train_image_model.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "train_image_model.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "O70d9EStDAsS"
      },
      "source": [
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras.utils import to_categorical\n",
        "from keras.callbacks import EarlyStopping\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Dense, Dropout, Activation, Flatten\n",
        "from keras.layers import Conv2D, MaxPooling2D, BatchNormalization\n",
        "from keras.losses import categorical_crossentropy\n",
        "from sklearn.metrics import accuracy_score\n",
        "from tensorflow.keras.optimizers import Adam\n",
        "from keras.regularizers import l2\n",
        "from keras.preprocessing.image import ImageDataGenerator\n",
        "from sklearn.metrics import classification_report, confusion_matrix\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VdTBHecADEyh",
        "outputId": "7a1a81a9-7e37-4e0c-8ef8-e2460e9c96c7"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U3XVZX8ODFwq",
        "outputId": "e83d98e2-2c5f-4d1d-883a-2e7d2ceb036d"
      },
      "source": [
        "path = '/content/drive/MyDrive/face_reg_dataset/fer2013.csv'\n",
        "data = pd.read_csv(path)\n",
        "#check data shape\n",
        "data.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(35887, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SB3pPGkBDHHe",
        "outputId": "72f00894-36b4-41eb-d667-9806bae1943b"
      },
      "source": [
        "data.Usage.value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Training       28709\n",
              "PublicTest      3589\n",
              "PrivateTest     3589\n",
              "Name: Usage, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "tm7wlfmsDIPM",
        "outputId": "98201bb6-1e65-4ef6-b343-ef43ee371a23"
      },
      "source": [
        "emotion_map = {0: 'Angry', 1: 'Digust', 2: 'Fear', 3: 'Happy', 4: 'Sad', 5: 'Surprise', 6: 'Neutral'}\n",
        "emotion_counts = data['emotion'].value_counts(sort=False).reset_index()\n",
        "emotion_counts.columns = ['emotion', 'number']\n",
        "emotion_counts['emotion'] = emotion_counts['emotion'].map(emotion_map)\n",
        "emotion_counts"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>emotion</th>\n",
              "      <th>number</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Angry</td>\n",
              "      <td>4953</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Digust</td>\n",
              "      <td>547</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Fear</td>\n",
              "      <td>5121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Happy</td>\n",
              "      <td>8989</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Sad</td>\n",
              "      <td>6077</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Surprise</td>\n",
              "      <td>4002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Neutral</td>\n",
              "      <td>6198</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    emotion  number\n",
              "0     Angry    4953\n",
              "1    Digust     547\n",
              "2      Fear    5121\n",
              "3     Happy    8989\n",
              "4       Sad    6077\n",
              "5  Surprise    4002\n",
              "6   Neutral    6198"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "xpGWjpVyDLBe",
        "outputId": "825742e8-bda4-47e5-a911-8d2e94fa9fe7"
      },
      "source": [
        "plt.figure(figsize=(6,4))\n",
        "sns.barplot(emotion_counts.emotion, emotion_counts.number)\n",
        "plt.title('Class distribution')\n",
        "plt.ylabel('Number', fontsize=12)\n",
        "plt.xlabel('Emotions', fontsize=12)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 831
        },
        "id": "UqGwgoqFDMUn",
        "outputId": "5bac55b2-5b9f-432e-f997-142601f3c49d"
      },
      "source": [
        "def row2image(row):\n",
        "    pixels, emotion = row['pixels'], emotion_map[row['emotion']]\n",
        "    img = np.array(pixels.split())\n",
        "    img = img.reshape(48,48)\n",
        "    image = np.zeros((48,48,3))\n",
        "    image[:,:,0] = img\n",
        "    image[:,:,1] = img\n",
        "    image[:,:,2] = img\n",
        "    return np.array([image.astype(np.uint8), emotion])\n",
        "\n",
        "plt.figure(0, figsize=(16,10))\n",
        "for i in range(1,8):\n",
        "    face = data[data['emotion'] == i-1].iloc[0]\n",
        "    img = row2image(face)\n",
        "    plt.subplot(2,4,i)\n",
        "    plt.imshow(img[0])\n",
        "    plt.title(img[1])\n",
        "\n",
        "plt.show() "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n",
            "  if __name__ == '__main__':\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x720 with 7 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Iau2jco-DMow",
        "outputId": "2244cae9-bee6-4073-914d-58ce21b18408"
      },
      "source": [
        "data_train = data[data['Usage']=='Training'].copy()\n",
        "data_val   = data[data['Usage']=='PublicTest'].copy()\n",
        "data_test  = data[data['Usage']=='PrivateTest'].copy()\n",
        "print(\"train shape: {}, \\nvalidation shape: {}, \\ntest shape: {}\".format(data_train.shape, data_val.shape, data_test.shape))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "train shape: (28709, 3), \n",
            "validation shape: (3589, 3), \n",
            "test shape: (3589, 3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "id": "9-Sc_E-1DOax",
        "outputId": "bcf5f529-3538-4195-e910-a23787e29d62"
      },
      "source": [
        "emotion_labels = ['Angry', 'Digust', 'Fear', 'Happy', 'Sad', 'Surprise', 'Neutral']\n",
        "\n",
        "def setup_axe(axe,df,title):\n",
        "    df['emotion'].value_counts(sort=False).plot(ax=axe, kind='bar', rot=0)\n",
        "    axe.set_xticklabels(emotion_labels)\n",
        "    axe.set_xlabel(\"Emotions\")\n",
        "    axe.set_ylabel(\"Number\")\n",
        "    axe.set_title(title)\n",
        "    \n",
        "    # set individual bar lables using above list\n",
        "    for i in axe.patches:\n",
        "        # get_x pulls left or right; get_height pushes up or down\n",
        "        axe.text(i.get_x()-.05, i.get_height()+120, \\\n",
        "                str(round((i.get_height()), 2)), fontsize=14, color='dimgrey',\n",
        "                    rotation=0)\n",
        "\n",
        "   \n",
        "fig, axes = plt.subplots(1,3, figsize=(20,8), sharey=True)\n",
        "setup_axe(axes[0],data_train,'train')\n",
        "setup_axe(axes[1],data_val,'validation')\n",
        "setup_axe(axes[2],data_test,'test')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 3 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0-hAqMHtDPwG"
      },
      "source": [
        "num_classes = 7 \n",
        "width, height = 48, 48\n",
        "num_epochs = 50\n",
        "batch_size = 64\n",
        "num_features = 64"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bdVMYeNSDZ3u",
        "outputId": "f967432d-ce4a-4ef7-d9b3-03c5f2ac06cd"
      },
      "source": [
        "# CRNO stands for Convert, Reshape, Normalize, One-hot encoding\n",
        "# (i) convert strings to lists of integers\n",
        "# (ii) reshape and normalise grayscale image with 255.0\n",
        "# (iii) one-hot encoding label, e.g. class 3 to [0,0,0,1,0,0,0]\n",
        "\n",
        "def CRNO(df, dataName):\n",
        "    df['pixels'] = df['pixels'].apply(lambda pixel_sequence: [int(pixel) for pixel in pixel_sequence.split()])\n",
        "    data_X = np.array(df['pixels'].tolist(), dtype='float32').reshape(-1,width, height,1)/255.0   \n",
        "    data_Y = to_categorical(df['emotion'], num_classes)  \n",
        "    print(dataName, \"_X shape: {}, \", dataName, \"_Y shape: {}\".format(data_X.shape, data_Y.shape))\n",
        "    return data_X, data_Y\n",
        "\n",
        "    \n",
        "train_X, train_Y = CRNO(data_train, \"train\") #training data\n",
        "val_X, val_Y     = CRNO(data_val, \"val\") #validation data\n",
        "test_X, test_Y   = CRNO(data_test, \"test\") #test data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "train _X shape: {},  train _Y shape: (28709, 48, 48, 1)\n",
            "val _X shape: {},  val _Y shape: (3589, 48, 48, 1)\n",
            "test _X shape: {},  test _Y shape: (3589, 48, 48, 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AU7G0-pQDbKy",
        "outputId": "f8434b06-aee5-4479-bf01-e869c39f2c24"
      },
      "source": [
        "model = Sequential()\n",
        "\n",
        "#module 1\n",
        "model.add(Conv2D(2*2*num_features, kernel_size=(3, 3), input_shape=(width, height, 1), data_format='channels_last'))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "model.add(Conv2D(2*2*num_features, kernel_size=(3, 3), padding='same'))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))\n",
        "\n",
        "#module 2\n",
        "model.add(Conv2D(2*num_features, kernel_size=(3, 3), padding='same'))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "model.add(Conv2D(2*num_features, kernel_size=(3, 3), padding='same'))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))\n",
        "\n",
        "#module 3\n",
        "model.add(Conv2D(num_features, kernel_size=(3, 3), padding='same'))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "model.add(Conv2D(num_features, kernel_size=(3, 3), padding='same'))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))\n",
        "\n",
        "#flatten\n",
        "model.add(Flatten())\n",
        "\n",
        "#dense 1\n",
        "model.add(Dense(2*2*2*num_features))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "\n",
        "#dense 2\n",
        "model.add(Dense(2*2*num_features))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "\n",
        "#dense 3\n",
        "model.add(Dense(2*num_features))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Activation('relu'))\n",
        "\n",
        "#output layer\n",
        "model.add(Dense(num_classes, activation='softmax'))\n",
        "\n",
        "model.compile(loss='categorical_crossentropy', \n",
        "              optimizer=Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-7), \n",
        "              metrics=['accuracy'])\n",
        "\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d (Conv2D)             (None, 46, 46, 256)       2560      \n",
            "                                                                 \n",
            " batch_normalization (BatchN  (None, 46, 46, 256)      1024      \n",
            " ormalization)                                                   \n",
            "                                                                 \n",
            " activation (Activation)     (None, 46, 46, 256)       0         \n",
            "                                                                 \n",
            " conv2d_1 (Conv2D)           (None, 46, 46, 256)       590080    \n",
            "                                                                 \n",
            " batch_normalization_1 (Batc  (None, 46, 46, 256)      1024      \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_1 (Activation)   (None, 46, 46, 256)       0         \n",
            "                                                                 \n",
            " max_pooling2d (MaxPooling2D  (None, 23, 23, 256)      0         \n",
            " )                                                               \n",
            "                                                                 \n",
            " conv2d_2 (Conv2D)           (None, 23, 23, 128)       295040    \n",
            "                                                                 \n",
            " batch_normalization_2 (Batc  (None, 23, 23, 128)      512       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_2 (Activation)   (None, 23, 23, 128)       0         \n",
            "                                                                 \n",
            " conv2d_3 (Conv2D)           (None, 23, 23, 128)       147584    \n",
            "                                                                 \n",
            " batch_normalization_3 (Batc  (None, 23, 23, 128)      512       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_3 (Activation)   (None, 23, 23, 128)       0         \n",
            "                                                                 \n",
            " max_pooling2d_1 (MaxPooling  (None, 11, 11, 128)      0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " conv2d_4 (Conv2D)           (None, 11, 11, 64)        73792     \n",
            "                                                                 \n",
            " batch_normalization_4 (Batc  (None, 11, 11, 64)       256       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_4 (Activation)   (None, 11, 11, 64)        0         \n",
            "                                                                 \n",
            " conv2d_5 (Conv2D)           (None, 11, 11, 64)        36928     \n",
            "                                                                 \n",
            " batch_normalization_5 (Batc  (None, 11, 11, 64)       256       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_5 (Activation)   (None, 11, 11, 64)        0         \n",
            "                                                                 \n",
            " max_pooling2d_2 (MaxPooling  (None, 5, 5, 64)         0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 1600)              0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 512)               819712    \n",
            "                                                                 \n",
            " batch_normalization_6 (Batc  (None, 512)              2048      \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_6 (Activation)   (None, 512)               0         \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 256)               131328    \n",
            "                                                                 \n",
            " batch_normalization_7 (Batc  (None, 256)              1024      \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_7 (Activation)   (None, 256)               0         \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 128)               32896     \n",
            "                                                                 \n",
            " batch_normalization_8 (Batc  (None, 128)              512       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " activation_8 (Activation)   (None, 128)               0         \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 7)                 903       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 2,137,991\n",
            "Trainable params: 2,134,407\n",
            "Non-trainable params: 3,584\n",
            "_________________________________________________________________\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/adam.py:105: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n",
            "  super(Adam, self).__init__(name, **kwargs)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2SKjmM1tDdYb",
        "outputId": "c059ce5a-bb84-4dc5-879e-4f2a7e8c8323"
      },
      "source": [
        "# data generator\n",
        "data_generator = ImageDataGenerator(\n",
        "                        featurewise_center=False,\n",
        "                        featurewise_std_normalization=False,\n",
        "                        rotation_range=10,\n",
        "                        width_shift_range=0.1,\n",
        "                        height_shift_range=0.1,\n",
        "                        zoom_range=.1,\n",
        "                        horizontal_flip=True)\n",
        "\n",
        "\n",
        "es = EarlyStopping(monitor='val_loss', patience = 10, mode = 'min', restore_best_weights=True)\n",
        "\n",
        "history = model.fit_generator(data_generator.flow(train_X, train_Y, batch_size),\n",
        "                                steps_per_epoch=len(train_X) / batch_size,\n",
        "                                epochs=num_epochs,\n",
        "                                verbose=2, \n",
        "                                callbacks = [es],\n",
        "                                validation_data=(val_X, val_Y))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:19: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/50\n",
            "448/448 - 101s - loss: 1.6604 - accuracy: 0.3439 - val_loss: 1.8102 - val_accuracy: 0.2848 - 101s/epoch - 224ms/step\n",
            "Epoch 2/50\n",
            "448/448 - 85s - loss: 1.3786 - accuracy: 0.4663 - val_loss: 1.3529 - val_accuracy: 0.4728 - 85s/epoch - 189ms/step\n",
            "Epoch 3/50\n",
            "448/448 - 85s - loss: 1.2431 - accuracy: 0.5251 - val_loss: 1.4871 - val_accuracy: 0.4224 - 85s/epoch - 190ms/step\n",
            "Epoch 4/50\n",
            "448/448 - 85s - loss: 1.1716 - accuracy: 0.5553 - val_loss: 1.2638 - val_accuracy: 0.5358 - 85s/epoch - 189ms/step\n",
            "Epoch 5/50\n",
            "448/448 - 85s - loss: 1.1225 - accuracy: 0.5724 - val_loss: 1.4326 - val_accuracy: 0.4876 - 85s/epoch - 189ms/step\n",
            "Epoch 6/50\n",
            "448/448 - 85s - loss: 1.0844 - accuracy: 0.5893 - val_loss: 1.2157 - val_accuracy: 0.5508 - 85s/epoch - 189ms/step\n",
            "Epoch 7/50\n",
            "448/448 - 85s - loss: 1.0558 - accuracy: 0.6001 - val_loss: 1.2351 - val_accuracy: 0.5422 - 85s/epoch - 189ms/step\n",
            "Epoch 8/50\n",
            "448/448 - 85s - loss: 1.0316 - accuracy: 0.6098 - val_loss: 1.0789 - val_accuracy: 0.5974 - 85s/epoch - 189ms/step\n",
            "Epoch 9/50\n",
            "448/448 - 85s - loss: 1.0032 - accuracy: 0.6215 - val_loss: 1.2002 - val_accuracy: 0.5673 - 85s/epoch - 189ms/step\n",
            "Epoch 10/50\n",
            "448/448 - 85s - loss: 0.9887 - accuracy: 0.6277 - val_loss: 1.0959 - val_accuracy: 0.5979 - 85s/epoch - 189ms/step\n",
            "Epoch 11/50\n",
            "448/448 - 85s - loss: 0.9642 - accuracy: 0.6356 - val_loss: 1.1242 - val_accuracy: 0.5874 - 85s/epoch - 189ms/step\n",
            "Epoch 12/50\n",
            "448/448 - 85s - loss: 0.9452 - accuracy: 0.6415 - val_loss: 1.0336 - val_accuracy: 0.6199 - 85s/epoch - 189ms/step\n",
            "Epoch 13/50\n",
            "448/448 - 85s - loss: 0.9297 - accuracy: 0.6484 - val_loss: 1.0453 - val_accuracy: 0.6105 - 85s/epoch - 189ms/step\n",
            "Epoch 14/50\n",
            "448/448 - 85s - loss: 0.9074 - accuracy: 0.6573 - val_loss: 1.0821 - val_accuracy: 0.6032 - 85s/epoch - 188ms/step\n",
            "Epoch 15/50\n",
            "448/448 - 85s - loss: 0.9032 - accuracy: 0.6582 - val_loss: 1.0774 - val_accuracy: 0.5968 - 85s/epoch - 189ms/step\n",
            "Epoch 16/50\n",
            "448/448 - 85s - loss: 0.8857 - accuracy: 0.6649 - val_loss: 1.1063 - val_accuracy: 0.6155 - 85s/epoch - 188ms/step\n",
            "Epoch 17/50\n",
            "448/448 - 86s - loss: 0.8704 - accuracy: 0.6708 - val_loss: 1.0274 - val_accuracy: 0.6227 - 86s/epoch - 193ms/step\n",
            "Epoch 18/50\n",
            "448/448 - 86s - loss: 0.8590 - accuracy: 0.6742 - val_loss: 1.0365 - val_accuracy: 0.6233 - 86s/epoch - 192ms/step\n",
            "Epoch 19/50\n",
            "448/448 - 85s - loss: 0.8372 - accuracy: 0.6869 - val_loss: 1.0651 - val_accuracy: 0.6102 - 85s/epoch - 189ms/step\n",
            "Epoch 20/50\n",
            "448/448 - 85s - loss: 0.8294 - accuracy: 0.6883 - val_loss: 1.1116 - val_accuracy: 0.6138 - 85s/epoch - 189ms/step\n",
            "Epoch 21/50\n",
            "448/448 - 85s - loss: 0.8157 - accuracy: 0.6938 - val_loss: 0.9865 - val_accuracy: 0.6514 - 85s/epoch - 189ms/step\n",
            "Epoch 22/50\n",
            "448/448 - 85s - loss: 0.8045 - accuracy: 0.6965 - val_loss: 1.0636 - val_accuracy: 0.6191 - 85s/epoch - 188ms/step\n",
            "Epoch 23/50\n",
            "448/448 - 85s - loss: 0.7855 - accuracy: 0.7061 - val_loss: 1.0936 - val_accuracy: 0.6141 - 85s/epoch - 189ms/step\n",
            "Epoch 24/50\n",
            "448/448 - 85s - loss: 0.7732 - accuracy: 0.7081 - val_loss: 0.9765 - val_accuracy: 0.6481 - 85s/epoch - 188ms/step\n",
            "Epoch 25/50\n",
            "448/448 - 84s - loss: 0.7672 - accuracy: 0.7105 - val_loss: 1.0187 - val_accuracy: 0.6445 - 84s/epoch - 188ms/step\n",
            "Epoch 26/50\n",
            "448/448 - 85s - loss: 0.7518 - accuracy: 0.7162 - val_loss: 0.9967 - val_accuracy: 0.6467 - 85s/epoch - 189ms/step\n",
            "Epoch 27/50\n",
            "448/448 - 84s - loss: 0.7405 - accuracy: 0.7227 - val_loss: 1.0062 - val_accuracy: 0.6484 - 84s/epoch - 188ms/step\n",
            "Epoch 28/50\n",
            "448/448 - 85s - loss: 0.7285 - accuracy: 0.7244 - val_loss: 1.0231 - val_accuracy: 0.6445 - 85s/epoch - 189ms/step\n",
            "Epoch 29/50\n",
            "448/448 - 86s - loss: 0.7216 - accuracy: 0.7274 - val_loss: 1.0045 - val_accuracy: 0.6442 - 86s/epoch - 192ms/step\n",
            "Epoch 30/50\n",
            "448/448 - 85s - loss: 0.7098 - accuracy: 0.7347 - val_loss: 1.0880 - val_accuracy: 0.6358 - 85s/epoch - 188ms/step\n",
            "Epoch 31/50\n",
            "448/448 - 86s - loss: 0.6901 - accuracy: 0.7396 - val_loss: 1.0060 - val_accuracy: 0.6539 - 86s/epoch - 192ms/step\n",
            "Epoch 32/50\n",
            "448/448 - 85s - loss: 0.6821 - accuracy: 0.7436 - val_loss: 1.0461 - val_accuracy: 0.6436 - 85s/epoch - 189ms/step\n",
            "Epoch 33/50\n",
            "448/448 - 85s - loss: 0.6724 - accuracy: 0.7492 - val_loss: 1.0538 - val_accuracy: 0.6406 - 85s/epoch - 189ms/step\n",
            "Epoch 34/50\n",
            "448/448 - 85s - loss: 0.6546 - accuracy: 0.7561 - val_loss: 1.0401 - val_accuracy: 0.6378 - 85s/epoch - 188ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
        },
        "id": "1vJw6tdADfKM",
        "outputId": "10d58272-70ca-41f4-a35a-9718eda3b751"
      },
      "source": [
        "fig, axes = plt.subplots(1,2, figsize=(18, 6))\n",
        "# Plot training & validation accuracy values\n",
        "axes[0].plot(history.history['accuracy'])\n",
        "axes[0].plot(history.history['val_accuracy'])\n",
        "axes[0].set_title('Model accuracy')\n",
        "axes[0].set_ylabel('Accuracy')\n",
        "axes[0].set_xlabel('Epoch')\n",
        "axes[0].legend(['Train', 'Validation'], loc='upper left')\n",
        "\n",
        "# Plot training & validation loss values\n",
        "axes[1].plot(history.history['loss'])\n",
        "axes[1].plot(history.history['val_loss'])\n",
        "axes[1].set_title('Model loss')\n",
        "axes[1].set_ylabel('Loss')\n",
        "axes[1].set_xlabel('Epoch')\n",
        "axes[1].legend(['Train', 'Validation'], loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tAkyPm_PQEnj",
        "outputId": "97a3c22f-e50f-4014-87d1-c918f04ddaee"
      },
      "source": [
        "test_true = np.argmax(test_Y, axis=1)\n",
        "test_pred = np.argmax(model.predict(test_X), axis=1)\n",
        "print(\"CNN Model Accuracy on test set: {:.4f}\".format(accuracy_score(test_true, test_pred)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CNN Model Accuracy on test set: 0.6651\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cYvRe3jdDgWK"
      },
      "source": [
        "def plot_confusion_matrix(y_true, y_pred, classes,\n",
        "                          normalize=False,\n",
        "                          title=None,\n",
        "                          cmap=plt.cm.Blues):\n",
        "    \"\"\"\n",
        "    This function prints and plots the confusion matrix.\n",
        "    Normalization can be applied by setting `normalize=True`.\n",
        "    \"\"\"\n",
        "    if not title:\n",
        "        if normalize:\n",
        "            title = 'Normalized confusion matrix'\n",
        "        else:\n",
        "            title = 'Confusion matrix, without normalization'\n",
        "\n",
        "    # Compute confusion matrix\n",
        "    cm = confusion_matrix(y_true, y_pred)\n",
        "    # Only use the labels that appear in the data\n",
        "    classes = classes\n",
        "    if normalize:\n",
        "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
        "        #print(\"Normalized confusion matrix\")\n",
        "    #else:\n",
        "        #print('Confusion matrix, without normalization')\n",
        "\n",
        "    #print(cm)\n",
        "\n",
        "    fig, ax = plt.subplots(figsize=(12,6))\n",
        "    im = ax.imshow(cm, interpolation='nearest', cmap=cmap)\n",
        "    ax.figure.colorbar(im, ax=ax)\n",
        "    # We want to show all ticks...\n",
        "    ax.set(xticks=np.arange(cm.shape[1]),\n",
        "           yticks=np.arange(cm.shape[0]),\n",
        "           # ... and label them with the respective list entries\n",
        "           xticklabels=classes, yticklabels=classes,\n",
        "           title=title,\n",
        "           ylabel='True label',\n",
        "           xlabel='Predicted label')\n",
        "\n",
        "    # Rotate the tick labels and set their alignment.\n",
        "    plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
        "             rotation_mode=\"anchor\")\n",
        "\n",
        "    # Loop over data dimensions and create text annotations.\n",
        "    fmt = '.2f' if normalize else 'd'\n",
        "    thresh = cm.max() / 2.\n",
        "    for i in range(cm.shape[0]):\n",
        "        for j in range(cm.shape[1]):\n",
        "            ax.text(j, i, format(cm[i, j], fmt),\n",
        "                    ha=\"center\", va=\"center\",\n",
        "                    color=\"white\" if cm[i, j] > thresh else \"black\")\n",
        "    fig.tight_layout()\n",
        "    return ax"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "YSOv7kjEDidE",
        "outputId": "d085b1f3-7bc1-45f5-bc64-bf3133d5664d"
      },
      "source": [
        "# Plot normalized confusion matrix\n",
        "plot_confusion_matrix(test_true, test_pred, classes=emotion_labels, normalize=True, title='Normalized confusion matrix')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rAs321DmDjg_"
      },
      "source": [
        "model.save(\"model.h5\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V1evpw1RVNGh",
        "outputId": "21d1665e-b050-4b0e-ceb8-00dd5ed2f2f5"
      },
      "source": [
        "model.save('/content/drive/MyDrive/face_reg_dataset/model1')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "INFO:tensorflow:Assets written to: /content/drive/MyDrive/face_reg_dataset/model1/assets\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "67KUFm67DlAH",
        "outputId": "518b45d8-1caa-4e5c-dbea-0602671a2a25"
      },
      "source": [
        "model_json = model.to_json()\n",
        "with open(\"model.json\", \"w\") as json_file:\n",
        "  json_file.write(model_json)\n",
        "model.save_weights(\"model.h5\")\n",
        "print(\"Saved model to disk\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved model to disk\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q49KNF35R_w7"
      },
      "source": [
        "from keras.models import load_model\n",
        "model = load_model('example_model.h5')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JyaztpJ-U8cZ",
        "outputId": "204309ff-f0f0-4b25-a7c7-e9ff32105a6a"
      },
      "source": [
        "weights = model.get_weights()\n",
        "print(weights)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[array([[[[ 0.03977949, -0.0328359 , -0.00451388, ...,  0.01702523,\n",
            "           0.01370978,  0.03084408]],\n",
            "\n",
            "        [[ 0.03537728, -0.02410604, -0.03031775, ...,  0.00971295,\n",
            "           0.10911543,  0.06184788]],\n",
            "\n",
            "        [[ 0.04082606, -0.06042095, -0.11758865, ..., -0.07948714,\n",
            "           0.09735525,  0.1050942 ]]],\n",
            "\n",
            "\n",
            "       [[[-0.04655695,  0.1211309 ,  0.11960886, ...,  0.00635418,\n",
            "          -0.04981611, -0.0399268 ]],\n",
            "\n",
            "        [[ 0.04406901,  0.24324234,  0.1270348 , ..., -0.03993665,\n",
            "          -0.24825329, -0.09521511]],\n",
            "\n",
            "        [[ 0.04398527, -0.06587357, -0.03465717, ..., -0.05082601,\n",
            "          -0.15686126, -0.03864539]]],\n",
            "\n",
            "\n",
            "       [[[-0.08873909, -0.10004774, -0.01082278, ...,  0.00932294,\n",
            "           0.04358141, -0.10954417]],\n",
            "\n",
            "        [[-0.0856614 ,  0.05861927,  0.06061861, ...,  0.00092095,\n",
            "           0.12083842, -0.14860386]],\n",
            "\n",
            "        [[ 0.01004083, -0.08823736, -0.07920569, ...,  0.10814172,\n",
            "           0.07985458, -0.085802  ]]]], dtype=float32), array([ 2.02432158e-03,  4.13140692e-02,  1.15140351e-02, -3.70314866e-02,\n",
            "       -2.70163571e-03, -2.48522200e-02,  1.80888046e-02, -1.31082246e-02,\n",
            "       -2.49151848e-02, -1.76269375e-03, -7.47465864e-02,  7.29870005e-03,\n",
            "       -2.19697114e-02,  1.37748802e-02, -1.69076701e-03,  1.07079428e-02,\n",
            "       -5.08259423e-02,  3.33841518e-02, -1.49813760e-02,  4.37404774e-03,\n",
            "       -6.92953356e-03, -1.96511056e-02, -1.94959380e-02,  1.10274777e-02,\n",
            "       -9.20093677e-04, -1.97764188e-02,  2.53556948e-03,  3.15610366e-03,\n",
            "       -6.41055964e-03,  3.11543550e-02, -9.53820162e-03, -4.85518537e-02,\n",
            "        1.52881611e-02, -1.06272306e-02, -8.68763924e-02, -2.10691672e-02,\n",
            "        8.79372098e-03,  2.88722515e-02,  1.12450356e-03, -2.57374509e-03,\n",
            "        7.41738593e-03,  1.57912693e-03,  6.73394650e-04,  1.11107137e-02,\n",
            "        3.62719712e-03,  3.37015800e-02,  9.58663598e-03, -5.23820668e-02,\n",
            "        2.25263252e-03,  5.41888252e-02, -4.61116526e-03,  3.10085565e-02,\n",
            "        1.44975390e-02,  1.02190105e-02,  9.36753862e-03, -2.00478043e-02,\n",
            "        8.82752705e-04,  2.59760711e-02,  3.09944712e-03, -4.47266316e-03,\n",
            "        3.81080322e-02,  6.72163023e-03, -1.01798298e-02, -1.42550692e-01,\n",
            "        2.55069807e-02,  5.57029508e-02,  8.12679622e-03,  8.50541983e-03,\n",
            "        4.53957682e-03, -4.92859073e-02, -2.33141724e-02,  4.03086990e-02,\n",
            "        5.62434597e-03,  4.86017577e-03,  1.04392529e-04,  2.77106967e-02,\n",
            "       -3.02753728e-02,  2.62963143e-03,  7.74554792e-04, -7.06095994e-03,\n",
            "        2.60310732e-02,  3.98374908e-03, -2.04696991e-02, -4.51149652e-03,\n",
            "       -8.05243552e-02, -4.69783619e-02,  5.66034205e-03, -8.32669437e-03,\n",
            "       -1.92691032e-02,  5.67698851e-02, -2.65571810e-02,  1.26531965e-03,\n",
            "       -1.79681946e-02, -2.61824206e-02, -1.87383223e-04, -1.36214150e-02,\n",
            "       -1.61734540e-02,  1.92768592e-02,  4.08178940e-03, -1.47231687e-02,\n",
            "       -2.20231665e-03,  2.69859587e-03, -9.62054357e-03, -2.91021951e-02,\n",
            "       -3.74223031e-02,  4.13365941e-03, -2.17956584e-02, -3.73139977e-02,\n",
            "       -1.49735920e-02,  3.93231809e-02,  1.26837883e-02, -1.20529451e-03,\n",
            "       -4.18564770e-03, -2.16494240e-02,  1.85989980e-02, -1.31988898e-03,\n",
            "        9.14087240e-03, -4.31177160e-03,  6.18792186e-03,  9.36152507e-03,\n",
            "       -2.33279746e-02, -2.69898027e-02,  1.04379011e-02,  3.23184133e-02,\n",
            "        6.69773668e-03, -5.58775850e-04, -2.63736374e-03,  4.30897297e-03,\n",
            "       -2.83564776e-02,  3.85837839e-03,  1.09410370e-02, -2.56197853e-03,\n",
            "       -2.80230939e-02,  2.90194992e-02,  2.95014065e-02,  1.90052949e-02,\n",
            "        2.91943736e-02,  2.57303640e-02, -2.99419230e-03,  1.43867526e-02,\n",
            "        4.82635759e-03, -1.23064471e-02, -6.57225377e-04,  6.76302705e-03,\n",
            "        1.65068006e-04, -1.31491187e-03,  1.54765816e-02,  1.03480937e-02,\n",
            "       -2.50470527e-02,  1.00859748e-02,  8.38726163e-02,  1.04632583e-02,\n",
            "       -3.87518201e-03,  1.40807349e-02,  2.05229372e-02,  6.58201566e-03,\n",
            "        7.24651897e-03,  1.17549999e-03, -2.04795855e-03,  2.30278019e-02,\n",
            "        4.77644987e-03,  8.72155465e-03, -1.54678756e-02, -1.84693895e-02,\n",
            "        8.84333160e-04, -2.13673207e-04,  4.33586091e-02, -7.94692058e-03,\n",
            "        2.38046572e-02,  3.22642247e-03, -1.24921873e-02,  1.68377049e-02,\n",
            "        4.44496470e-03,  3.84753756e-02, -1.46256911e-03, -7.36208558e-02,\n",
            "       -1.58243068e-03, -3.38942334e-02, -1.49709722e-02,  1.52215110e-02,\n",
            "       -4.96737054e-03,  4.69148271e-02, -3.22347991e-02, -3.92558193e-03,\n",
            "        1.91439893e-02,  1.88537035e-02, -2.37136856e-02, -2.90417019e-03,\n",
            "        7.04535544e-02,  2.63672229e-02,  5.73457824e-03, -1.36391185e-02,\n",
            "       -1.58666261e-02, -1.57699306e-02,  1.34762023e-02,  4.22692262e-02,\n",
            "       -5.46017941e-03,  4.38205758e-03,  2.82696541e-02, -2.81124236e-03,\n",
            "       -8.30140803e-03, -7.31820799e-03,  2.63711018e-03,  4.24776413e-02,\n",
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            "       -6.02683611e-03, -9.19512510e-02, -2.25152206e-02,  8.68505042e-04,\n",
            "        3.92165454e-03,  3.70648480e-03,  3.10357800e-03, -8.45456496e-03,\n",
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            "       -3.77836451e-02,  3.18123922e-02, -9.44164395e-03, -1.13650728e-02,\n",
            "        3.06435451e-02, -5.16049797e-03, -1.84430601e-03,  1.80845428e-02,\n",
            "       -4.38453443e-03,  1.54977124e-02,  3.79832275e-03, -1.43331904e-02,\n",
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            "       -1.18244421e-02, -1.79694325e-03, -7.18306080e-02, -4.42747027e-03],\n",
            "      dtype=float32), array([0.44077072, 1.0787659 , 0.53056157, 1.1328659 , 0.5640619 ,\n",
            "       1.1066158 , 0.930551  , 0.6642294 , 0.9458944 , 0.7423829 ,\n",
            "       1.4421682 , 0.5345041 , 0.9975816 , 0.649106  , 0.6516784 ,\n",
            "       0.60106146, 0.8357604 , 0.83965737, 0.9167305 , 0.5513492 ,\n",
            "       0.71163595, 0.74443996, 0.6512402 , 0.45357382, 1.2039684 ,\n",
            "       0.47606292, 0.869368  , 0.4721029 , 0.5896443 , 1.1081282 ,\n",
            "       1.0698612 , 0.60043603, 1.0517179 , 0.7695956 , 1.0277413 ,\n",
            "       1.3447152 , 0.80107325, 0.5814438 , 0.54102176, 0.5291869 ,\n",
            "       0.76669765, 0.8676941 , 0.5183644 , 0.6581014 , 0.6744592 ,\n",
            "       0.74639547, 1.0626649 , 0.8631711 , 0.6188542 , 1.3459361 ,\n",
            "       0.70316887, 1.0900661 , 1.0800669 , 0.7228685 , 0.63456374,\n",
            "       0.84103614, 0.53876585, 1.1881387 , 1.1322138 , 0.58675927,\n",
            "       0.9286895 , 0.386098  , 0.7772128 , 1.93183   , 0.5939901 ,\n",
            "       1.1541455 , 0.4842347 , 0.59734595, 0.8171736 , 0.9973494 ,\n",
            "       0.99473655, 1.1133137 , 0.9349558 , 0.96496844, 0.6920857 ,\n",
            "       0.69765055, 1.1999857 , 0.79859585, 0.97021425, 0.57339704,\n",
            "       1.7641766 , 0.665801  , 1.1170559 , 0.8457068 , 1.3671035 ,\n",
            "       1.4406441 , 0.35974163, 0.8715583 , 0.9944905 , 0.8196672 ,\n",
            "       0.881305  , 0.6039466 , 1.0171801 , 0.8433044 , 0.74077666,\n",
            "       0.5197108 , 1.008862  , 0.6579408 , 0.51306665, 0.49906796,\n",
            "       0.58007574, 0.66426665, 0.9174888 , 1.0155948 , 1.2987419 ,\n",
            "       0.47983885, 0.6554174 , 0.86305463, 0.69374233, 0.930891  ,\n",
            "       0.8385406 , 0.4087777 , 0.53138006, 0.7592148 , 0.6584347 ,\n",
            "       1.2369839 , 0.6144615 , 0.6840286 , 0.66039115, 0.70058095,\n",
            "       0.5866115 , 0.65325177, 1.1459209 , 0.7496653 , 0.93834054,\n",
            "       0.8655776 , 0.49706757, 1.2607431 , 0.8632913 , 1.3215481 ,\n",
            "       0.43611923, 1.0384257 , 0.9353435 , 0.9161974 , 0.5577447 ,\n",
            "       0.4194763 , 0.78066885, 1.1070502 , 0.4469736 , 0.64135486,\n",
            "       0.6588635 , 0.6495381 , 0.87733877, 0.43870035, 0.60854954,\n",
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            "       1.4969676 , 1.0248233 , 0.57003593, 0.48603696, 0.912173  ,\n",
            "       0.91577256, 0.44776917, 0.94717056, 0.5113749 , 0.630753  ,\n",
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            "       0.59043694, 1.0263432 , 0.5344549 , 0.83486265, 0.8555714 ,\n",
            "       0.72497994, 0.5749743 , 0.38527158, 1.3916613 , 0.6075549 ,\n",
            "       0.9016114 , 0.9423404 , 0.71709675, 0.76271546, 0.87466824,\n",
            "       0.520701  , 1.2893375 , 0.8592808 , 0.6208439 , 0.9714299 ,\n",
            "       0.5235901 , 0.93412495, 0.5983079 , 1.3781198 , 1.1164725 ,\n",
            "       0.72003883, 0.6647403 , 0.97776175, 0.8374673 , 0.570387  ,\n",
            "       0.73646957, 0.78576297, 0.40958476, 1.0241853 , 0.5580878 ,\n",
            "       0.77089727, 0.5426501 , 0.41251397, 0.82899225, 1.3022348 ,\n",
            "       0.59769094, 0.8095394 , 0.6359036 , 0.37986335, 1.120322  ,\n",
            "       1.1326784 , 0.51714396, 0.64319247, 0.8907943 , 0.7233785 ,\n",
            "       1.1435043 , 0.6951125 , 1.2982862 , 1.2123908 , 0.57584214,\n",
            "       1.381969  , 0.7116714 , 0.5184732 , 0.54517436, 0.8087318 ,\n",
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            "       0.42927858, 0.78143173, 1.2398937 , 0.94592255, 0.741732  ,\n",
            "       0.43435866, 0.78622496, 0.49490348, 0.9422405 , 0.87075466,\n",
            "       0.54058135, 0.4981365 , 0.71379536, 0.80979854, 1.0684323 ,\n",
            "       0.6323846 , 0.7873515 , 0.6788997 , 1.0026556 , 0.5439782 ,\n",
            "       0.7907767 , 1.1031704 , 0.8250358 , 0.6246344 , 1.3179436 ,\n",
            "       0.87450624], dtype=float32), array([-0.17262812,  0.39925143,  0.12369771,  0.4255048 , -0.29093605,\n",
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            "        0.07573055,  0.3060883 , -0.13688238, -0.3781394 , -0.27534586,\n",
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            "       -0.48428613, -0.17377084, -0.02175805,  0.57482153, -0.2612125 ,\n",
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            "       -0.07348907, -0.11134366, -0.19514841, -0.39571986, -0.0421698 ,\n",
            "        0.45068938, -0.00978519,  0.56403506,  0.40413105,  0.04116023,\n",
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            "       -2.80246362e-02, -8.40403587e-02,  4.29695189e-01,  1.91703010e-02,\n",
            "       -1.61314309e-02, -2.78843373e-01,  5.82202664e-03, -2.75287721e-02,\n",
            "        1.26392972e-02,  1.37608480e-02,  4.35996093e-02,  1.85291134e-02,\n",
            "       -4.05062735e-02,  2.84046009e-02, -2.49309931e-03,  9.29743983e-03,\n",
            "        3.14680748e-02, -2.23729829e-03, -9.94596747e-04, -1.05982954e-02,\n",
            "       -1.05522154e-02,  4.72937338e-03, -9.74306371e-03, -1.22783640e-02,\n",
            "       -4.06944603e-02,  1.11352382e-02,  1.80956293e-02, -2.89084460e-03,\n",
            "        3.20258061e-03,  9.14840866e-03,  2.19391622e-02, -2.00907513e-02,\n",
            "        5.50646968e-02,  3.87964956e-02, -1.96195506e-02, -1.63786281e-02,\n",
            "        1.09926043e-02,  1.11548277e-02,  1.43709183e-02, -3.09291761e-02,\n",
            "        8.32462218e-03, -6.21353183e-03, -2.75717285e-02,  8.90039932e-03,\n",
            "       -2.25239083e-01, -2.12047175e-02, -7.45652989e-02, -1.92698017e-01],\n",
            "      dtype=float32), array([4.47565981e-04, 3.84577987e-04, 5.28954843e-04, 7.85564713e-04,\n",
            "       6.63509185e-04, 3.39123420e-04, 4.34275105e-04, 8.11618578e-04,\n",
            "       1.03096396e-03, 9.83420061e-04, 9.16922931e-04, 2.31025551e-04,\n",
            "       1.26269204e-03, 7.92955921e-04, 2.20251590e-04, 6.69770176e-04,\n",
            "       9.86525789e-04, 9.39224265e-04, 9.91824665e-04, 1.92675507e-05,\n",
            "       3.08153481e-04, 1.03669998e-03, 2.31008278e-04, 5.19844878e-04,\n",
            "       4.38901159e-04, 2.04261189e-04, 1.21027110e-02, 1.17398224e-04,\n",
            "       1.24492843e-04, 1.33761449e-03, 1.88318358e-04, 2.53406732e-04,\n",
            "       3.55043536e-04, 9.81640536e-04, 1.29077153e-03, 4.32283967e-04,\n",
            "       1.23935542e-03, 5.89769625e-04, 5.06723009e-04, 1.13486320e-04,\n",
            "       2.57138978e-04, 1.62787182e-04, 5.71949407e-04, 5.12276369e-04,\n",
            "       4.74833098e-04, 3.30576237e-04, 2.38915702e-04, 7.25969323e-04,\n",
            "       3.07698530e-04, 4.56867681e-04, 1.16924127e-03, 2.82910827e-04,\n",
            "       8.07806849e-04, 1.14401360e-03, 1.71318112e-04, 2.41717164e-04,\n",
            "       4.34405665e-05, 2.69567390e-04, 3.11302079e-04, 3.62473802e-05,\n",
            "       1.24506596e-02, 2.24285177e-04, 9.75545787e-04, 5.56188228e-04,\n",
            "       1.83510972e-04, 1.12125522e-03, 8.17611057e-04, 7.98789551e-04,\n",
            "       2.77684361e-04, 1.33603939e-03, 7.01053243e-04, 4.78396891e-04,\n",
            "       1.14466844e-03, 1.39550038e-03, 1.20953110e-03, 1.09560962e-03,\n",
            "       3.09408439e-04, 3.79345292e-04, 3.90625326e-04, 2.27671902e-04,\n",
            "       5.30450314e-04, 2.43173345e-04, 3.62188148e-04, 1.04073260e-03,\n",
            "       8.21915513e-04, 4.00147575e-04, 4.80664254e-04, 8.51815380e-03,\n",
            "       3.52124742e-04, 3.03632522e-04, 1.08231127e-03, 1.57386792e-04,\n",
            "       1.69748277e-03, 1.35433173e-03, 7.13457726e-03, 2.50840269e-04,\n",
            "       1.38046872e-03, 8.76826176e-04, 1.40011281e-04, 2.31865459e-04,\n",
            "       3.13918485e-04, 3.98111623e-03, 3.04625748e-04, 4.39442694e-04,\n",
            "       1.65667920e-03, 1.78016329e-04, 3.17596161e-04, 3.27808550e-04,\n",
            "       3.70369002e-04, 1.50527095e-03, 9.40929167e-04, 2.41718255e-04,\n",
            "       2.76250695e-03, 6.53203169e-04, 3.38330487e-04, 8.46298062e-04,\n",
            "       5.50734345e-04, 8.45893810e-04, 8.04024225e-04, 6.83607534e-04,\n",
            "       4.46297054e-04, 5.44157519e-04, 2.78593710e-04, 6.17582700e-04,\n",
            "       1.00980874e-03, 6.90926856e-04, 4.29005886e-04, 3.12507706e-04,\n",
            "       1.01673882e-03, 3.41795851e-04, 3.98848468e-04, 1.51910936e-03,\n",
            "       1.08748395e-03, 1.25929806e-03, 2.53803941e-04, 2.44352996e-04,\n",
            "       4.69966821e-04, 1.16636220e-03, 2.49428704e-04, 8.33832566e-03,\n",
            "       1.03149668e-03, 3.77089297e-03, 1.23250159e-03, 3.53918353e-04,\n",
            "       5.27791162e-05, 3.53588199e-04, 6.92394620e-04, 6.53674826e-04,\n",
            "       3.60224483e-04, 2.89111311e-04, 3.47372639e-04, 5.79305517e-04,\n",
            "       2.05611301e-04, 1.04941530e-04, 2.07960922e-02, 1.09292031e-03,\n",
            "       2.82075984e-04, 1.04201888e-03, 4.64517128e-04, 1.92404885e-04,\n",
            "       6.31976349e-04, 4.82922274e-04, 1.16457709e-03, 3.15063575e-04,\n",
            "       3.42191255e-04, 5.19286783e-04, 5.13168809e-04, 8.03100411e-04,\n",
            "       4.30889777e-04, 1.14224630e-03, 6.36681449e-03, 3.45011620e-04,\n",
            "       2.39743764e-04, 6.64205058e-04, 7.13703572e-04, 7.00210920e-04,\n",
            "       1.42631354e-03, 6.59156591e-04, 1.00592303e-03, 1.26878836e-03,\n",
            "       5.54889673e-04, 1.15698681e-03, 1.20091962e-03, 1.91341853e-04,\n",
            "       6.11104653e-04, 9.49542096e-04, 3.67969216e-04, 2.03409651e-03,\n",
            "       3.60860780e-04, 1.26590754e-03, 3.40448780e-04, 8.58146581e-04,\n",
            "       2.94824038e-02, 3.79287841e-04, 2.26414093e-04, 6.81067409e-04,\n",
            "       3.85635998e-04, 6.89188892e-05, 7.23422039e-04, 7.01837183e-04,\n",
            "       9.66284249e-04, 3.01448832e-04, 2.10574974e-04, 2.84933165e-04,\n",
            "       3.56434204e-04, 6.05690002e-04, 1.13848168e-02, 4.89945465e-04,\n",
            "       2.54425016e-04, 1.42076227e-03, 4.38705571e-02, 3.13661090e-04,\n",
            "       7.03516824e-04, 1.79271288e-02, 7.37374066e-04, 7.32939981e-04,\n",
            "       3.09174735e-04, 2.32055609e-04, 4.12285619e-04, 3.52379982e-04,\n",
            "       2.80986103e-04, 9.37596546e-04, 1.42236604e-04, 9.10541217e-04,\n",
            "       3.18989070e-04, 1.54407113e-04, 4.07606349e-05, 1.06281321e-03,\n",
            "       7.58561888e-04, 8.93395452e-04, 1.53569563e-04, 2.57323467e-04,\n",
            "       2.43332688e-04, 7.62998068e-04, 4.04832477e-04, 2.27306999e-04,\n",
            "       6.59992569e-04, 2.85757531e-04, 4.11946821e-04, 2.63788213e-04,\n",
            "       9.53371404e-04, 6.92390313e-04, 8.36950261e-04, 1.14839047e-03,\n",
            "       7.96003733e-04, 3.06130241e-04, 8.40121822e-04, 9.10689880e-04,\n",
            "       1.19797001e-03, 6.26972032e-05, 2.88746756e-04, 8.50990240e-04,\n",
            "       1.04628662e-02, 3.73763149e-04, 2.65264942e-04, 8.57026409e-03],\n",
            "      dtype=float32), array([[[[-3.86780687e-02, -3.37109305e-02,  7.52654392e-03, ...,\n",
            "          -3.68934423e-02, -3.46084982e-02, -8.41621403e-03],\n",
            "         [-1.25034913e-01, -1.56939104e-01,  7.08484184e-03, ...,\n",
            "          -6.83166832e-02, -1.49898259e-02, -5.78074530e-02],\n",
            "         [-3.71835716e-02, -5.83419614e-02, -4.14107852e-02, ...,\n",
            "          -6.54942691e-02, -6.99151829e-02, -5.16251400e-02],\n",
            "         ...,\n",
            "         [ 7.57134333e-02,  4.85548936e-02, -5.73548526e-02, ...,\n",
            "          -1.57433394e-02, -2.30571292e-02, -1.44040631e-03],\n",
            "         [ 1.52815953e-01, -6.66454155e-03, -4.03186046e-02, ...,\n",
            "          -7.94001669e-03,  2.98809428e-02, -7.47368932e-02],\n",
            "         [ 4.96287830e-02, -4.53492627e-02,  3.48627754e-02, ...,\n",
            "           7.81823024e-02,  5.33671416e-02, -9.71572176e-02]],\n",
            "\n",
            "        [[-3.83385047e-02, -8.92575085e-02, -1.39000290e-03, ...,\n",
            "           4.35061119e-02, -1.13269582e-01,  4.06281237e-04],\n",
            "         [-1.10168725e-01,  9.80293900e-02,  4.84379344e-02, ...,\n",
            "           4.70896810e-03, -1.53049871e-01, -1.64845902e-02],\n",
            "         [-2.82983575e-02, -4.79293708e-03, -4.98198867e-02, ...,\n",
            "          -7.63484091e-02, -6.09908141e-02, -1.83730852e-02],\n",
            "         ...,\n",
            "         [-1.79574359e-03,  1.82088874e-02, -5.95426606e-03, ...,\n",
            "          -6.38874099e-02, -7.47400988e-03,  1.60179995e-02],\n",
            "         [ 5.13638668e-02,  3.14194337e-02, -3.86927128e-02, ...,\n",
            "           3.59118804e-02,  3.83085124e-02, -4.11166884e-02],\n",
            "         [ 7.96363726e-02,  1.15748299e-02, -5.51395025e-03, ...,\n",
            "           1.00999348e-01,  6.48318082e-02, -9.59089324e-02]],\n",
            "\n",
            "        [[-9.06485915e-02,  7.55298650e-03, -1.16140777e-02, ...,\n",
            "           8.64027664e-02, -1.00518860e-01, -4.41547260e-02],\n",
            "         [-1.75203849e-02, -8.09095651e-02, -3.68207097e-02, ...,\n",
            "           2.01727338e-02,  2.03525741e-02,  3.68697904e-02],\n",
            "         [-5.11429086e-02,  5.96904289e-03, -1.03916623e-01, ...,\n",
            "          -1.79761031e-04,  6.68338835e-02,  4.53611910e-02],\n",
            "         ...,\n",
            "         [-3.27622588e-03,  2.53027007e-02,  1.40628684e-02, ...,\n",
            "          -1.16424672e-02,  7.80611904e-03, -8.44301656e-03],\n",
            "         [-6.50884435e-02,  5.83960116e-03, -5.53993471e-02, ...,\n",
            "           7.96619356e-02, -7.79628288e-04, -3.51128355e-02],\n",
            "         [ 3.37513946e-02, -9.67231765e-03,  4.38478636e-03, ...,\n",
            "           1.47755429e-01, -3.57205346e-02, -1.02082349e-01]]],\n",
            "\n",
            "\n",
            "       [[[ 2.35533770e-02, -4.77482863e-02, -6.98412210e-02, ...,\n",
            "          -4.27490212e-02, -4.69063073e-02,  3.88056450e-02],\n",
            "         [ 9.12336186e-02, -2.07745507e-01,  2.68734060e-02, ...,\n",
            "           7.98647944e-03, -6.68420568e-02,  1.90827604e-02],\n",
            "         [ 1.03602163e-01, -6.69174269e-02, -4.60784025e-02, ...,\n",
            "          -9.05582532e-02,  2.77770609e-02,  3.84725071e-02],\n",
            "         ...,\n",
            "         [ 2.99330306e-04,  4.50913757e-02,  1.34156952e-02, ...,\n",
            "          -5.19908592e-02,  1.19976820e-02,  1.96069200e-02],\n",
            "         [-2.26300210e-01, -2.78012659e-02,  5.32440245e-02, ...,\n",
            "           2.34471112e-02,  8.16489905e-02, -6.26569912e-02],\n",
            "         [ 8.79728496e-02, -2.16722284e-02,  3.68748652e-03, ...,\n",
            "           6.49231747e-02,  1.24553954e-02,  3.48941460e-02]],\n",
            "\n",
            "        [[ 3.61987762e-02, -7.28229433e-02,  2.85027386e-03, ...,\n",
            "           1.08623449e-02, -1.00548707e-01,  5.54744080e-02],\n",
            "         [ 1.03286825e-01,  1.71362504e-01, -3.98516692e-02, ...,\n",
            "           5.76646775e-02,  2.90383608e-03,  3.74430828e-02],\n",
            "         [ 7.10439980e-02, -3.50128114e-03, -1.47295175e-02, ...,\n",
            "          -6.96322545e-02,  1.38221588e-02,  8.24397877e-02],\n",
            "         ...,\n",
            "         [ 7.34927971e-03,  1.05320127e-03,  1.77945439e-02, ...,\n",
            "          -3.05975024e-02, -5.26573770e-02,  2.78697573e-02],\n",
            "         [-2.02296883e-01, -5.35705090e-02,  7.28237703e-02, ...,\n",
            "           3.95510085e-02,  6.40110299e-02, -6.22235239e-02],\n",
            "         [ 9.72658992e-02,  1.51920076e-02, -2.07436252e-02, ...,\n",
            "           1.13924712e-01, -2.19658576e-02,  2.45980714e-02]],\n",
            "\n",
            "        [[-9.06436937e-04,  1.99848432e-02, -2.37571113e-02, ...,\n",
            "           4.17663567e-02, -4.03766111e-02,  7.97873810e-02],\n",
            "         [ 9.13299397e-02, -3.45113985e-02, -8.08469653e-02, ...,\n",
            "           1.10677689e-01,  6.80790693e-02,  3.09123304e-02],\n",
            "         [ 1.56758707e-02,  1.22577883e-02, -6.27846420e-02, ...,\n",
            "          -8.01897794e-03,  7.19216242e-02,  6.81569800e-02],\n",
            "         ...,\n",
            "         [-3.50775346e-02,  8.30686390e-02, -1.31735466e-02, ...,\n",
            "          -4.92840912e-03, -2.85298731e-02,  3.76960100e-03],\n",
            "         [-5.22645675e-02,  2.07003169e-02,  3.56835723e-02, ...,\n",
            "           7.26297870e-02, -8.18017125e-02, -1.63988825e-02],\n",
            "         [ 3.19281667e-02,  6.50503561e-02,  1.34442365e-02, ...,\n",
            "           1.77183241e-01, -7.76009783e-02, -5.66730201e-02]]],\n",
            "\n",
            "\n",
            "       [[[-4.61335406e-02, -9.31052864e-02, -7.54435062e-02, ...,\n",
            "          -1.65897980e-02, -7.40916515e-03,  2.90745078e-03],\n",
            "         [ 4.06783521e-02, -1.30333632e-01,  5.20525351e-02, ...,\n",
            "           2.01255605e-02,  1.13767624e-01,  2.88229231e-02],\n",
            "         [-3.49784233e-02, -5.41374497e-02, -2.32688375e-02, ...,\n",
            "          -1.06927320e-01,  9.40215290e-02,  6.07433431e-02],\n",
            "         ...,\n",
            "         [ 3.73609848e-02,  1.59749184e-02, -5.72700873e-02, ...,\n",
            "           6.68729132e-04,  1.35718454e-02, -8.41738563e-03],\n",
            "         [ 1.68947175e-01, -5.19037955e-02, -1.02719285e-01, ...,\n",
            "          -6.24450408e-02, -1.19854219e-01, -6.29508719e-02],\n",
            "         [ 1.76087990e-02, -8.99227038e-02, -9.07922313e-02, ...,\n",
            "           4.32017706e-02, -4.32511494e-02,  2.25569904e-02]],\n",
            "\n",
            "        [[-5.01027405e-02, -7.50917243e-04, -9.61069688e-02, ...,\n",
            "           4.13754731e-02, -3.35613899e-02,  6.64673075e-02],\n",
            "         [-1.05596356e-01,  3.58059816e-02,  4.78934273e-02, ...,\n",
            "          -5.51671423e-02,  8.02545846e-02, -2.00143433e-04],\n",
            "         [-7.60236830e-02,  5.24242176e-03,  4.15954106e-02, ...,\n",
            "          -9.72451121e-02,  9.42344218e-02,  5.83132952e-02],\n",
            "         ...,\n",
            "         [ 7.43676350e-02, -4.80646081e-02,  1.32328682e-02, ...,\n",
            "           2.93995291e-02, -6.34996071e-02,  1.78841362e-03],\n",
            "         [ 2.29996011e-01,  9.73143894e-03, -6.76502660e-02, ...,\n",
            "           7.13779777e-03, -8.71749818e-02, -3.08079571e-02],\n",
            "         [ 1.55385714e-02, -2.58515701e-02, -5.68872392e-02, ...,\n",
            "           8.93202275e-02, -2.05046721e-02, -2.54408084e-02]],\n",
            "\n",
            "        [[-4.91804443e-02, -4.13007140e-02, -5.64084500e-02, ...,\n",
            "           9.06207319e-03, -5.91966473e-02,  4.12949659e-02],\n",
            "         [-5.47298752e-02,  4.58889492e-02, -1.67206768e-02, ...,\n",
            "           6.01709075e-02,  1.11008532e-01,  2.30355375e-02],\n",
            "         [ 3.30641633e-03,  1.50947385e-02,  3.45169306e-02, ...,\n",
            "          -7.18444632e-03,  3.95044535e-02,  1.11175455e-01],\n",
            "         ...,\n",
            "         [-2.70133112e-02, -2.07474288e-02, -1.80576295e-02, ...,\n",
            "           4.53426912e-02, -8.33875593e-03,  2.47580442e-03],\n",
            "         [ 9.88705680e-02, -1.35870026e-02,  1.16358008e-02, ...,\n",
            "           1.58181321e-02, -7.55207762e-02,  1.14195300e-02],\n",
            "         [ 1.38191078e-02, -5.88357300e-02, -9.66880694e-02, ...,\n",
            "           1.06939919e-01,  2.92005930e-02, -5.88826463e-02]]]],\n",
            "      dtype=float32), array([ 4.97221306e-04, -6.96777308e-04,  1.63352553e-04, -7.54364359e-04,\n",
            "       -1.55987495e-04, -5.12587612e-05, -2.25989643e-04,  1.20075427e-04,\n",
            "       -2.74313032e-04,  3.87620967e-04,  1.74686320e-05, -1.65599980e-04,\n",
            "       -5.97236445e-04, -2.34627485e-04, -8.80261010e-04,  6.77239615e-04,\n",
            "       -1.85679601e-04, -6.23942411e-04,  1.65118108e-04,  4.64034558e-04,\n",
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            "        5.42895868e-04, -3.66245862e-04,  3.28140741e-04, -7.66980462e-04,\n",
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            "        -2.6136494 , -19.821213  , -19.074846  ,   9.218978  ,\n",
            "        -4.725462  ,  -5.717754  ,  -4.5640616 ,  -7.1686835 ,\n",
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            "       -17.880419  ,  -3.252422  , -12.896772  , -12.785716  ,\n",
            "       -11.096804  ,  -5.4783373 , -18.399006  ,  -7.3051376 ,\n",
            "         0.62492114,  -2.8162858 ,  29.576857  ,   8.409402  ,\n",
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            "        -7.4913774 ,  -2.6275387 ,  14.759031  , -15.414629  ,\n",
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            "        -7.808413  , -13.110603  , -16.245565  ,  -3.1176214 ,\n",
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            "       -15.102862  , -14.229239  , -17.15046   ,   2.1949143 ],\n",
            "      dtype=float32), array([ 94.47145 ,  48.742226, 120.33451 , 121.64866 ,  60.730675,\n",
            "        82.66386 , 107.31684 , 106.92303 , 123.98878 , 181.98872 ,\n",
            "       128.15277 , 137.97897 ,  92.5915  ,  99.29004 , 134.12993 ,\n",
            "        95.605896, 143.72629 ,  97.96911 ,  60.56159 , 115.767   ,\n",
            "        83.04474 ,  83.1279  ,  96.07545 , 167.4488  ,  89.41561 ,\n",
            "       146.41754 , 112.005974, 217.33803 , 150.92381 ,  84.85263 ,\n",
            "       142.62534 , 101.81858 ,  66.71352 , 104.06261 ,  80.67331 ,\n",
            "       197.39961 , 117.48158 , 165.26    ,  68.247856, 158.69492 ,\n",
            "        48.12986 ,  84.4811  , 102.63125 , 106.51164 ,  79.94775 ,\n",
            "        58.768974, 125.70374 , 120.75706 , 182.46643 , 150.28206 ,\n",
            "       101.43895 ,  61.894497, 105.33474 ,  88.51913 ,  76.09753 ,\n",
            "       105.64952 ,  93.54583 , 103.73458 ,  87.75591 , 173.48961 ,\n",
            "       171.91077 , 135.98431 ,  85.10303 , 172.67957 ,  70.568665,\n",
            "       125.40603 ,  93.52634 , 193.38087 , 108.32832 ,  98.89765 ,\n",
            "        78.88837 ,  73.575745,  49.683968, 116.86429 , 113.5191  ,\n",
            "       108.80471 , 115.53739 , 141.23344 ,  64.92348 , 102.98908 ,\n",
            "        91.57985 , 115.716194,  91.68963 , 133.92142 ,  91.6892  ,\n",
            "       102.66976 , 115.64178 , 152.36299 , 129.68271 , 117.176636,\n",
            "       202.72624 , 181.60341 ,  91.90364 , 109.2522  , 112.20256 ,\n",
            "       126.79875 , 134.32297 , 231.98073 ,  83.61776 , 134.93887 ,\n",
            "       108.79308 , 201.2309  ,  98.852646, 116.59064 , 139.09305 ,\n",
            "        87.97173 ,  57.20318 ,  63.2851  , 115.843445,  95.309975,\n",
            "       145.84792 , 122.57975 , 157.21208 , 110.63125 ,  99.48514 ,\n",
            "       106.20614 , 152.3307  , 151.99574 , 125.24975 , 192.29944 ,\n",
            "       177.0797  ,  99.535835, 100.550964, 113.12663 ,  94.42142 ,\n",
            "       168.1703  , 139.03575 , 151.8363  , 103.40874 , 191.2563  ,\n",
            "        58.080715, 214.80786 , 190.40479 ,  98.30692 , 114.422066,\n",
            "       135.19319 ,  88.157234, 210.59164 , 191.89282 , 135.8287  ,\n",
            "       101.04293 , 120.814285, 114.410446,  90.38303 , 176.53406 ,\n",
            "        90.609886, 155.49658 , 221.87752 , 167.69388 ,  63.992405,\n",
            "       128.78307 , 134.00862 , 113.578285, 199.82263 , 100.28065 ,\n",
            "        97.977356,  72.166504,  89.5422  , 137.42143 ,  99.65618 ,\n",
            "       111.66558 , 133.9622  , 109.28558 ,  89.85302 , 108.311485,\n",
            "        49.164795,  75.11792 , 111.52268 ,  81.50072 , 138.0665  ,\n",
            "        77.91793 , 107.15294 ,  51.237198,  74.80864 , 141.18097 ,\n",
            "       112.63796 , 203.69576 ,  78.12187 , 138.37184 ,  89.264656,\n",
            "       109.50597 ,  64.237144, 147.55177 , 108.13491 , 120.677635,\n",
            "        83.26659 , 108.83981 ,  55.034393, 108.45461 ,  75.894196,\n",
            "       173.40111 ,  77.2651  , 133.22539 , 134.42705 , 144.68794 ,\n",
            "       163.09229 , 137.88002 ,  98.90298 , 151.24377 , 151.22952 ,\n",
            "        96.40477 , 109.47935 ,  75.27905 ,  92.00144 ,  86.929634,\n",
            "       107.584435, 165.10196 , 211.25557 , 110.677475, 132.97455 ,\n",
            "        94.29345 , 116.76936 , 109.130714,  74.00567 ,  90.22198 ,\n",
            "       127.20987 , 113.734085, 134.83276 , 117.76068 , 119.87216 ,\n",
            "       186.10785 , 104.26521 , 110.79034 ,  81.4502  , 167.69102 ,\n",
            "       149.76334 ,  83.30124 ,  60.80657 ,  50.976948, 189.36978 ,\n",
            "       155.91383 , 117.759346, 141.73459 , 125.161736,  89.23556 ,\n",
            "       157.90541 , 164.19638 , 112.909065, 114.35191 , 233.44415 ,\n",
            "       113.38624 ,  82.10529 ,  97.138565,  44.6817  , 109.06689 ,\n",
            "        83.76067 , 159.50063 , 174.65971 , 102.71086 , 106.94241 ,\n",
            "       159.95834 ,  76.39858 , 114.857025, 168.7406  ,  92.649635,\n",
            "        55.605133], dtype=float32), array([[[[-2.55373120e-03,  6.63449196e-03, -1.26941860e-01, ...,\n",
            "          -1.56874880e-01,  4.92018014e-02,  1.08125478e-01],\n",
            "         [ 4.81634634e-04, -3.67890000e-02, -1.58419535e-01, ...,\n",
            "           7.30606839e-02,  4.18059118e-02,  1.72247201e-01],\n",
            "         [-9.02764574e-02, -9.54140946e-02,  3.24225575e-02, ...,\n",
            "           1.08333994e-02,  1.36133358e-02,  2.52574291e-02],\n",
            "         ...,\n",
            "         [ 1.20614119e-01,  3.95492204e-02, -8.19918048e-03, ...,\n",
            "           4.97825928e-02, -3.78644764e-02,  8.84437710e-02],\n",
            "         [ 8.07782933e-02, -1.53445512e-01,  6.67780563e-02, ...,\n",
            "           7.36251324e-02, -5.71363093e-03,  4.47566994e-02],\n",
            "         [-4.95838076e-02,  3.22162099e-02, -3.54592279e-02, ...,\n",
            "          -3.85826528e-02,  1.01924516e-01, -8.04430526e-03]],\n",
            "\n",
            "        [[ 8.47179145e-02, -8.15444216e-02, -8.00101459e-02, ...,\n",
            "          -1.87982902e-01,  4.44980152e-02, -3.11474800e-02],\n",
            "         [-1.22113116e-01, -4.28602286e-02, -1.46048158e-01, ...,\n",
            "           4.97830659e-03,  1.38959801e-02,  7.40795061e-02],\n",
            "         [ 1.89162605e-02, -7.43121142e-03,  2.28553787e-02, ...,\n",
            "          -1.05113477e-01, -9.19524860e-03,  6.62292317e-02],\n",
            "         ...,\n",
            "         [ 8.48912522e-02, -2.04887409e-02, -7.94691741e-02, ...,\n",
            "          -3.36552821e-02,  3.11426762e-02,  4.82328534e-02],\n",
            "         [ 5.90319335e-02, -4.93038446e-02, -4.77316864e-02, ...,\n",
            "           4.91634421e-02, -1.14988610e-01, -2.46461872e-02],\n",
            "         [-5.21550514e-02,  2.95931175e-02, -7.01057687e-02, ...,\n",
            "          -1.55003425e-02,  2.44340906e-03, -6.87175393e-02]],\n",
            "\n",
            "        [[ 3.60180885e-02, -2.09622718e-02, -1.43617755e-02, ...,\n",
            "          -2.02154905e-01,  9.15449783e-02, -2.45903544e-02],\n",
            "         [-5.92940720e-04, -1.06215999e-01, -2.66740434e-02, ...,\n",
            "           5.49810380e-03,  1.86096076e-02,  1.22543573e-01],\n",
            "         [ 5.88066466e-02,  4.03003879e-02, -1.23482943e-02, ...,\n",
            "          -3.03380582e-02,  4.04230878e-02,  7.07051083e-02],\n",
            "         ...,\n",
            "         [ 2.69746389e-02, -6.65615946e-02, -2.45352432e-01, ...,\n",
            "          -4.21403535e-03,  1.53988432e-02,  6.85833097e-02],\n",
            "         [-3.26511599e-02, -5.55875488e-02,  1.94399823e-02, ...,\n",
            "           7.40801618e-02, -2.58932859e-02, -3.25189978e-02],\n",
            "         [ 2.51932926e-02, -4.89017218e-02, -5.19760996e-02, ...,\n",
            "          -1.19160794e-01,  1.84171461e-02, -6.29964098e-03]]],\n",
            "\n",
            "\n",
            "       [[[ 8.91972780e-02, -1.33612277e-02, -8.34582895e-02, ...,\n",
            "          -7.82230124e-02,  3.55597325e-02,  2.31101234e-02],\n",
            "         [ 6.93611801e-02,  4.29773517e-02, -5.24673425e-02, ...,\n",
            "           7.83429071e-02, -1.21594772e-01,  3.55389565e-02],\n",
            "         [-5.89431375e-02, -4.83491011e-02, -2.44889176e-04, ...,\n",
            "          -2.70295143e-03,  6.39237389e-02,  1.34564415e-01],\n",
            "         ...,\n",
            "         [-3.89486328e-02,  4.47938219e-02, -2.77942717e-02, ...,\n",
            "           2.95328852e-02,  2.95320041e-02,  3.22895721e-02],\n",
            "         [-6.26448914e-02, -6.03610277e-02, -3.16199288e-02, ...,\n",
            "           9.52770635e-02, -2.33583823e-02,  1.01974130e-01],\n",
            "         [-1.51980162e-01,  1.60729308e-02,  1.05653200e-02, ...,\n",
            "          -7.69950747e-02, -3.92781049e-02,  4.66480618e-03]],\n",
            "\n",
            "        [[ 8.73417109e-02, -1.39775649e-01, -5.28048836e-02, ...,\n",
            "           1.13247968e-01,  3.56140845e-02,  4.56867628e-02],\n",
            "         [-4.80303615e-02,  1.34958476e-01, -1.39340207e-01, ...,\n",
            "           5.76313473e-02, -6.06223978e-02,  5.85659333e-02],\n",
            "         [ 4.72844951e-02, -2.30251858e-03,  2.44031311e-03, ...,\n",
            "          -9.81435701e-02,  7.41674826e-02,  8.28650147e-02],\n",
            "         ...,\n",
            "         [-1.39866667e-02, -5.33052953e-03, -1.66063264e-01, ...,\n",
            "           1.98525079e-02,  1.26507692e-02,  2.64619887e-02],\n",
            "         [-2.69047860e-02, -5.71611002e-02,  9.81486030e-03, ...,\n",
            "           6.01616614e-02, -6.81425110e-02,  5.15618250e-02],\n",
            "         [-1.35961324e-01, -8.59110791e-04, -5.44230565e-02, ...,\n",
            "          -7.85700679e-02, -7.33658522e-02, -5.11842594e-02]],\n",
            "\n",
            "        [[ 1.19159617e-01, -1.64734155e-01, -6.18510991e-02, ...,\n",
            "          -1.26648974e-02, -1.18363518e-02, -2.83741076e-02],\n",
            "         [-1.13402903e-01,  7.01927673e-03, -1.60806343e-01, ...,\n",
            "          -9.00625996e-03, -1.49369225e-01,  3.20611447e-02],\n",
            "         [ 4.43368144e-02, -3.19827124e-02, -4.16881517e-02, ...,\n",
            "          -1.43624470e-01,  1.04282640e-01,  4.71133515e-02],\n",
            "         ...,\n",
            "         [ 2.78746132e-02, -2.80434405e-03, -1.70114577e-01, ...,\n",
            "           4.49977703e-02,  2.67570857e-02, -1.41309435e-02],\n",
            "         [-1.58587527e-02,  5.02898768e-02,  8.59986320e-02, ...,\n",
            "          -3.78847979e-02, -2.99976245e-02,  7.35492110e-02],\n",
            "         [-2.50044614e-02, -2.32234364e-03, -2.00660322e-02, ...,\n",
            "          -3.76914628e-02, -5.60399108e-02, -5.64033054e-02]]],\n",
            "\n",
            "\n",
            "       [[[-4.60376292e-02,  2.09144816e-01,  2.37669665e-02, ...,\n",
            "           1.77500725e-01,  7.17254542e-03, -9.81363431e-02],\n",
            "         [ 3.03197742e-01,  1.29860016e-02,  4.89738584e-02, ...,\n",
            "           1.60110280e-01, -9.07333940e-02, -3.01289782e-02],\n",
            "         [ 4.79887426e-02, -9.23330430e-03, -1.93195138e-02, ...,\n",
            "           1.54766276e-01,  8.10739473e-02, -4.84284647e-02],\n",
            "         ...,\n",
            "         [-6.79449737e-02,  2.50944532e-02,  4.08350397e-03, ...,\n",
            "           1.00867733e-01,  8.05627927e-02,  5.32389916e-02],\n",
            "         [ 1.81516428e-02, -1.68878213e-03, -4.30813804e-02, ...,\n",
            "           2.05699410e-02,  6.88248202e-02,  1.43852662e-02],\n",
            "         [-1.51741160e-02, -2.63468036e-03, -3.54935341e-02, ...,\n",
            "          -9.51873288e-02,  3.49793909e-03,  2.51775980e-02]],\n",
            "\n",
            "        [[ 6.26372918e-02, -5.49929077e-03,  1.23683088e-01, ...,\n",
            "           6.64558634e-02, -1.53202191e-01, -1.46358699e-01],\n",
            "         [ 7.08943382e-02,  1.05811015e-01,  1.69185996e-02, ...,\n",
            "           1.64208591e-01, -1.02811195e-01, -5.54401204e-02],\n",
            "         [ 1.22823112e-01,  3.24663073e-02,  6.66953996e-03, ...,\n",
            "           8.15480798e-02,  1.20911904e-01, -1.50193557e-01],\n",
            "         ...,\n",
            "         [-2.61932462e-02, -2.99909301e-02,  1.31961191e-02, ...,\n",
            "           8.71718228e-02,  8.59189332e-02,  4.37974446e-02],\n",
            "         [ 1.50996202e-03,  7.10091367e-02, -8.75722244e-03, ...,\n",
            "          -8.78581703e-02,  1.05597340e-01,  4.93040383e-02],\n",
            "         [ 2.24477127e-02,  9.27729905e-02, -4.38580737e-02, ...,\n",
            "          -1.27869457e-01, -6.19947128e-02,  3.88936745e-03]],\n",
            "\n",
            "        [[ 8.66517425e-02, -1.05463699e-01,  1.20293885e-01, ...,\n",
            "          -6.02449253e-02, -1.71131760e-01, -1.27733439e-01],\n",
            "         [ 1.66743007e-02,  9.26449373e-02, -1.29655734e-01, ...,\n",
            "           8.91883373e-02, -8.91849175e-02, -8.91130492e-02],\n",
            "         [ 2.30946718e-03, -4.36623208e-03, -2.22389828e-02, ...,\n",
            "           1.03907734e-01,  8.15521628e-02, -2.00125039e-01],\n",
            "         ...,\n",
            "         [-1.71015114e-02, -9.90979746e-02,  4.28743437e-02, ...,\n",
            "           1.18046746e-01,  5.50343245e-02,  2.26761010e-02],\n",
            "         [ 6.45797625e-02,  1.00760534e-01,  8.99112895e-02, ...,\n",
            "          -1.52578652e-01,  6.40011504e-02, -1.48914941e-03],\n",
            "         [ 4.06368561e-02,  4.72422875e-02, -8.19028467e-02, ...,\n",
            "          -5.86897731e-02, -4.85338643e-02, -8.50174502e-02]]]],\n",
            "      dtype=float32), array([-1.10754727e-05,  7.88871112e-05,  7.71733350e-04, -2.02112904e-04,\n",
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            "        1.26843093e-04, -1.37848867e-04,  1.41322394e-04, -3.42437590e-04,\n",
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            "        1.35395952e-04,  7.58391689e-05,  1.47932669e-05,  2.58009881e-04,\n",
            "        4.03545186e-04,  1.30233884e-05,  1.94025604e-04, -2.89655436e-04,\n",
            "        2.35968531e-04,  7.41968252e-05,  1.94188222e-04,  3.99308556e-06,\n",
            "        2.36460735e-04,  1.12786445e-04,  4.29674023e-04,  8.25553216e-05,\n",
            "       -3.00242478e-04,  5.38631102e-05,  1.03760445e-04,  4.29627653e-05,\n",
            "       -2.59196822e-04,  2.35040236e-04, -2.54315732e-04,  2.38150271e-04,\n",
            "        7.92529536e-05, -1.12699643e-04,  4.02118952e-04,  1.82669581e-04,\n",
            "        6.93335678e-05,  1.85731507e-04,  3.94601993e-05, -4.59895120e-04,\n",
            "        1.98076887e-04,  8.29441415e-05,  9.41491598e-05,  2.53890816e-04,\n",
            "        3.97537689e-04,  5.91155956e-04,  1.09096516e-04,  7.13076326e-04,\n",
            "       -7.64449069e-05, -2.11687016e-04,  1.84121978e-04, -2.16391418e-04,\n",
            "       -4.82627402e-05, -3.61463579e-04,  1.20930126e-04,  2.10252343e-04,\n",
            "       -2.27081000e-05, -4.51969572e-05, -1.14702962e-04, -3.07039358e-04,\n",
            "       -3.11418087e-04, -3.84414074e-04, -3.37759178e-04, -1.74485889e-04,\n",
            "       -2.61033711e-04,  1.58760304e-04,  1.17261683e-04,  7.23217963e-05,\n",
            "       -5.72989520e-04,  2.67566094e-04, -1.84263816e-04,  1.06198146e-04,\n",
            "       -9.03901091e-05, -1.89521852e-05, -2.82863184e-05, -2.93056743e-04,\n",
            "       -1.18393538e-04, -1.12844595e-04, -2.87330826e-04, -2.53166159e-04,\n",
            "       -1.52247012e-04, -3.62813385e-04,  4.28053987e-04,  1.64418176e-04,\n",
            "       -6.26560213e-05,  1.19796488e-04,  7.18217983e-04, -4.73674532e-04,\n",
            "       -5.05780044e-04, -3.68246489e-04, -3.20095496e-05,  3.99179320e-04,\n",
            "        1.21202705e-04, -1.00506404e-04,  1.54826957e-05, -9.18839723e-05,\n",
            "       -1.61990698e-04,  5.30700549e-04,  1.29923923e-04, -4.93719825e-04,\n",
            "       -1.66526472e-04,  1.90425286e-04,  3.51469003e-04,  7.47588201e-05,\n",
            "       -2.34709660e-04, -9.10190793e-05,  8.63635887e-06,  3.15431244e-04],\n",
            "      dtype=float32), array([1.0078793 , 1.0563546 , 0.9946462 , 1.200908  , 1.1944743 ,\n",
            "       0.8681127 , 1.0744909 , 0.8585676 , 1.023348  , 0.97096145,\n",
            "       0.9897058 , 0.90305996, 0.9166663 , 0.83886504, 1.0414654 ,\n",
            "       1.0258806 , 0.9827065 , 0.9550227 , 1.0284572 , 0.9240005 ,\n",
            "       0.9935619 , 1.052016  , 0.898238  , 0.97863185, 0.9311362 ,\n",
            "       1.0036265 , 1.0109599 , 0.9900088 , 1.039487  , 1.0184321 ,\n",
            "       0.91403174, 0.8811055 , 1.1201718 , 0.8923335 , 0.86716795,\n",
            "       0.94825333, 1.0259833 , 1.0996654 , 0.93670857, 0.87715036,\n",
            "       0.9277624 , 0.93452823, 1.0286334 , 0.92704487, 0.9272123 ,\n",
            "       0.9109819 , 0.76687735, 0.79350233, 0.90180457, 0.8725821 ,\n",
            "       1.0601412 , 0.84236944, 0.8664228 , 0.9829222 , 0.92148584,\n",
            "       0.7411632 , 0.9691873 , 0.9339713 , 1.0468292 , 1.1638305 ,\n",
            "       0.87147427, 0.8634088 , 0.89388174, 0.8580826 , 1.266618  ,\n",
            "       1.1917593 , 1.1706399 , 1.1894381 , 1.0521678 , 1.0123757 ,\n",
            "       0.7287762 , 0.9554727 , 0.95084685, 0.90922457, 0.9930269 ,\n",
            "       1.1205045 , 1.0857118 , 0.87451434, 0.94022614, 1.0020647 ,\n",
            "       1.2026087 , 0.96515244, 1.183779  , 0.9316449 , 0.99693924,\n",
            "       0.79948306, 0.8225219 , 0.89614093, 1.0445238 , 1.0523446 ,\n",
            "       0.9339954 , 1.0441144 , 0.8129019 , 1.0947534 , 0.9655358 ,\n",
            "       0.9677812 , 0.9555057 , 1.0994159 , 0.90339977, 0.96229494,\n",
            "       0.9754761 , 0.91365755, 0.8763532 , 1.0897112 , 0.97929054,\n",
            "       0.9370762 , 1.0807178 , 1.1537433 , 1.0667841 , 1.1108564 ,\n",
            "       1.0479277 , 0.9104735 , 1.0086303 , 0.90940684, 1.0299654 ,\n",
            "       0.9556896 , 1.023935  , 1.044278  , 1.0689318 , 1.0640787 ,\n",
            "       0.9076438 , 0.8200569 , 0.89819115, 0.7507457 , 0.9892301 ,\n",
            "       0.8650728 , 0.95609826, 1.0357887 ], dtype=float32), array([-0.17027317, -0.13937081, -0.19958675, -0.02574299, -0.28331974,\n",
            "       -0.4409629 , -0.21493983, -0.3262885 , -0.15326706, -0.33090085,\n",
            "       -0.18049826, -0.19158031, -0.3572633 , -0.273121  , -0.3099443 ,\n",
            "       -0.12329917, -0.28405136, -0.17221676, -0.1395651 , -0.1894458 ,\n",
            "       -0.17594711, -0.07455847, -0.26392198, -0.284294  , -0.25280806,\n",
            "       -0.06968248, -0.27714795, -0.29450253, -0.24244213, -0.27810535,\n",
            "       -0.2923388 , -0.1929887 , -0.07889419, -0.32943615, -0.28975728,\n",
            "       -0.4007832 , -0.215144  , -0.03093869, -0.17077637, -0.3500904 ,\n",
            "       -0.2689493 , -0.1885013 , -0.15654187, -0.21151873, -0.2223673 ,\n",
            "       -0.29716673, -0.25285822, -0.32705235, -0.14328417, -0.3549601 ,\n",
            "       -0.28533536, -0.3620889 , -0.29474002, -0.35955805, -0.22451693,\n",
            "       -0.47150707, -0.1422576 , -0.16342539, -0.13598974, -0.05369568,\n",
            "       -0.21433558, -0.29488537, -0.28841382, -0.23744749, -0.42111206,\n",
            "       -0.07758087, -0.1440363 , -0.05137453, -0.28306794, -0.23917381,\n",
            "       -0.45375016, -0.20874566, -0.15945914, -0.2661571 , -0.23545489,\n",
            "       -0.1892012 , -0.08834609, -0.326724  , -0.24249454, -0.34252885,\n",
            "       -0.07183035, -0.3578171 , -0.13259359, -0.24179392, -0.32862338,\n",
            "       -0.24400716, -0.37538633, -0.31523576, -0.18106252, -0.38511238,\n",
            "       -0.27435908, -0.17026615, -0.3491141 , -0.2062681 , -0.21683869,\n",
            "       -0.1570919 , -0.18205556, -0.14127654, -0.1363983 , -0.16724683,\n",
            "       -0.16567956, -0.33641934, -0.28341886, -0.22179265, -0.21030615,\n",
            "       -0.15313046, -0.01393187, -0.21217287, -0.19481559, -0.36817157,\n",
            "       -0.10243964, -0.37547073, -0.13451095, -0.35408148, -0.30870426,\n",
            "       -0.2043562 , -0.27885154, -0.21365555, -0.27426946, -0.13511527,\n",
            "       -0.26728877, -0.27741173, -0.28392184, -0.36401528, -0.27787367,\n",
            "       -0.36515433, -0.24057427, -0.08710891], dtype=float32), array([  1.7442873 , -12.978202  ,  -4.9141574 ,  -4.241666  ,\n",
            "        -7.4263506 ,   3.7182062 ,  -3.7558386 ,  -5.6679034 ,\n",
            "        -6.9943285 ,  -7.1231704 ,   0.32504663,  -6.247849  ,\n",
            "        -4.5912604 ,  -5.467119  ,  -9.821697  , -13.381782  ,\n",
            "       -12.182321  ,  -3.8771868 ,  -9.688952  ,   2.7184172 ,\n",
            "        -4.907864  , -14.148211  ,  -3.4108489 ,  -7.7976594 ,\n",
            "       -10.176451  ,  -3.096138  ,  -2.9721007 , -11.339886  ,\n",
            "        -5.7534924 ,   3.4861715 ,  -9.229819  ,  -8.769282  ,\n",
            "        -4.782726  ,  -3.2652216 ,  -8.051801  ,  -9.152826  ,\n",
            "        -4.964388  ,  -2.5265567 ,  -6.435693  ,  -9.418149  ,\n",
            "        -5.857042  ,  -9.970573  ,  -3.8474417 , -20.86664   ,\n",
            "        -7.108638  , -11.606188  ,  -5.2370143 , -15.661025  ,\n",
            "         5.5002522 , -13.228495  , -10.519028  ,  -9.594759  ,\n",
            "         0.47236022,  -5.359338  , -10.360326  ,  -8.299134  ,\n",
            "        -6.6336517 ,  -7.4065704 ,  -0.17301385, -10.74355   ,\n",
            "        -7.78397   ,  -3.79005   ,  -0.6679811 , -12.985526  ,\n",
            "        -6.716024  ,  -2.0460525 ,  -8.011394  ,  -6.800142  ,\n",
            "        -9.918292  ,  -8.279056  ,  -6.5817347 , -10.360658  ,\n",
            "       -14.196936  ,  -9.093395  ,  -8.163413  , -17.82397   ,\n",
            "        -9.752726  ,  -6.100332  , -15.565893  ,  -7.714085  ,\n",
            "        -8.759989  , -16.174376  ,  -6.144278  , -10.704947  ,\n",
            "        -9.580057  , -25.812475  ,   1.5843242 ,  10.196884  ,\n",
            "        -3.0127623 ,  -5.1469083 ,  -6.632109  ,  -8.252807  ,\n",
            "         3.256622  , -12.946605  , -10.139277  ,  -8.101673  ,\n",
            "        -5.502887  ,  -8.645844  ,  -8.532623  ,  -9.246161  ,\n",
            "        -8.799803  ,  -3.387689  ,  -7.8634777 ,  -6.044295  ,\n",
            "        -7.045347  ,  -3.4674175 ,  -6.048896  ,  -7.309283  ,\n",
            "        -3.4301949 ,  -9.274917  , -12.752679  ,  -8.91106   ,\n",
            "        -9.563142  , -10.819134  , -11.250299  , -16.761683  ,\n",
            "        -6.960871  ,  -9.06419   ,  -2.9216156 ,  -8.683537  ,\n",
            "         2.6426828 , -13.242275  , -10.597169  ,  -2.5343196 ,\n",
            "        -8.277493  ,  -6.097326  , -14.795507  ,  -9.595172  ],\n",
            "      dtype=float32), array([149.18097 , 224.26715 , 126.62096 , 122.09927 , 147.49437 ,\n",
            "       115.57679 , 110.71639 , 192.62883 , 171.89006 , 147.19112 ,\n",
            "        90.412445, 135.54091 , 123.124596, 169.0954  ,  95.69292 ,\n",
            "       304.1174  , 195.73647 , 123.40448 , 133.37628 , 188.25536 ,\n",
            "       199.35931 , 270.57452 , 175.56902 , 199.68277 , 191.34111 ,\n",
            "       106.43805 , 182.08849 , 244.88371 , 154.91127 , 152.49304 ,\n",
            "       202.53798 , 173.41032 , 111.19831 , 144.50603 , 161.05125 ,\n",
            "       182.69926 , 201.87062 , 166.14815 , 230.37007 , 151.3544  ,\n",
            "       143.71153 , 133.72914 , 165.81961 , 299.78482 , 237.90515 ,\n",
            "       209.23166 , 134.61993 , 250.57524 , 168.68428 , 173.1475  ,\n",
            "       147.92107 , 181.85019 , 166.38373 , 176.78621 , 174.29213 ,\n",
            "       178.4466  , 139.02312 , 211.29875 , 115.342804, 190.57205 ,\n",
            "       159.86572 , 122.45409 , 177.43466 , 214.23936 ,  84.25205 ,\n",
            "       169.55441 , 209.76047 , 128.59383 , 162.74849 , 241.532   ,\n",
            "       145.38615 , 201.11218 , 266.25177 , 251.43282 , 155.73921 ,\n",
            "       315.64728 , 196.13521 , 173.43402 , 401.96228 , 249.69453 ,\n",
            "       210.53368 , 319.96707 , 155.93526 , 241.69191 , 228.29062 ,\n",
            "       389.00223 , 143.36601 , 177.40927 , 157.10269 , 103.83662 ,\n",
            "       125.945244, 197.07869 , 164.13573 , 315.8037  , 272.88943 ,\n",
            "       207.3991  , 134.50592 , 239.70343 , 192.46228 , 189.7062  ,\n",
            "       125.65782 , 139.81023 , 176.0137  , 100.887276, 184.34706 ,\n",
            "       171.526   , 123.969536, 158.3428  , 140.95523 , 171.72598 ,\n",
            "       256.16562 , 232.97874 , 178.8877  , 155.24918 , 211.01555 ,\n",
            "       235.54097 , 181.49747 , 112.22797 , 105.96179 , 183.68459 ,\n",
            "       133.89027 , 211.85558 , 196.27608 , 143.53484 , 160.67638 ,\n",
            "       161.57683 , 336.33173 , 216.0477  ], dtype=float32), array([[[[-4.70855720e-02, -7.48556480e-02, -6.12150840e-02, ...,\n",
            "          -1.02721453e-01, -9.96546522e-02, -4.62148786e-02],\n",
            "         [ 5.81598915e-02,  9.85714495e-02,  1.36349658e-02, ...,\n",
            "          -9.68630463e-02,  6.06868602e-02,  6.45915940e-02],\n",
            "         [ 3.23585398e-03, -4.43729311e-02, -1.51226014e-01, ...,\n",
            "          -1.70473039e-01, -1.22325853e-01,  8.79358724e-02],\n",
            "         ...,\n",
            "         [ 5.24427332e-02,  5.05849943e-02, -4.04027849e-02, ...,\n",
            "          -6.92475736e-02, -6.13688901e-02, -5.29951788e-02],\n",
            "         [-7.91554153e-03, -1.43988822e-02, -2.68168170e-02, ...,\n",
            "          -4.51993793e-02,  3.02524939e-02, -1.25776410e-01],\n",
            "         [-1.79398537e-01, -8.46417900e-03,  1.44069597e-01, ...,\n",
            "          -4.09285277e-02, -1.99799072e-02, -1.19605079e-01]],\n",
            "\n",
            "        [[-1.01636082e-01, -3.32208499e-02, -1.27489790e-01, ...,\n",
            "           8.26626122e-02, -7.89803416e-02, -1.79177642e-01],\n",
            "         [ 1.35574475e-01,  2.25522250e-01,  3.30426022e-02, ...,\n",
            "          -7.19454288e-02,  1.12905033e-01,  1.75132632e-01],\n",
            "         [ 1.30992100e-01, -6.95071146e-02, -4.52914797e-02, ...,\n",
            "          -6.74143210e-02, -8.80695134e-02, -2.47807056e-03],\n",
            "         ...,\n",
            "         [ 1.29288271e-01, -4.03761640e-02, -9.91530716e-03, ...,\n",
            "           3.52757052e-02,  5.15358374e-02,  3.46711986e-02],\n",
            "         [-7.86364824e-03,  2.77838111e-02, -1.64761588e-01, ...,\n",
            "           1.15095444e-01,  1.10328130e-01, -5.51823433e-03],\n",
            "         [-9.17026252e-02, -1.29394829e-01,  7.88611099e-02, ...,\n",
            "          -1.10587496e-02, -5.53483032e-02, -1.51604623e-01]],\n",
            "\n",
            "        [[-4.71670814e-02,  9.03990958e-03, -6.24032058e-02, ...,\n",
            "           4.30226736e-02, -5.21235913e-02, -2.00672820e-01],\n",
            "         [ 1.43295079e-01,  1.11392498e-01, -8.74011219e-02, ...,\n",
            "          -8.25025886e-02,  2.04770878e-01,  3.76770347e-02],\n",
            "         [-4.38210033e-02, -5.62506989e-02, -1.46421522e-01, ...,\n",
            "          -1.27724499e-01, -2.52524763e-02, -2.48272941e-02],\n",
            "         ...,\n",
            "         [ 6.80103377e-02,  4.96805273e-02, -6.10531904e-02, ...,\n",
            "          -6.81887567e-03,  3.05689424e-02, -1.35136187e-01],\n",
            "         [ 9.19863675e-03, -1.13092653e-01, -8.33239257e-02, ...,\n",
            "          -6.10818230e-02,  6.78636730e-02,  1.29608303e-01],\n",
            "         [-1.03535220e-01, -1.47617593e-01,  3.78597324e-04, ...,\n",
            "          -1.11149296e-01, -8.73740837e-02, -4.08512168e-02]]],\n",
            "\n",
            "\n",
            "       [[[-1.20903052e-01,  5.41699491e-03, -2.22946241e-01, ...,\n",
            "          -2.47498099e-02,  7.70495608e-02, -5.63792810e-02],\n",
            "         [ 6.24217205e-02,  1.26605064e-01,  8.69990289e-02, ...,\n",
            "           6.16700090e-02,  1.44908056e-01,  3.29258256e-02],\n",
            "         [-7.91466087e-02, -2.07566470e-03, -1.20806713e-02, ...,\n",
            "          -9.07811448e-02,  4.00411896e-02,  6.35327771e-02],\n",
            "         ...,\n",
            "         [-2.32190508e-02, -1.59661934e-01, -3.07370245e-01, ...,\n",
            "           2.97067892e-02,  5.58472648e-02,  2.37114541e-02],\n",
            "         [-6.86194822e-02, -9.90191028e-02,  3.87659594e-02, ...,\n",
            "          -3.05115879e-02,  1.04977764e-01,  9.22919661e-02],\n",
            "         [-1.87900871e-01,  8.51464942e-02,  8.28832462e-02, ...,\n",
            "          -2.94768903e-02,  1.98935084e-02, -9.47426558e-02]],\n",
            "\n",
            "        [[-1.33627355e-01, -8.28689486e-02, -1.30759701e-01, ...,\n",
            "           2.23400071e-02,  6.80508092e-02, -2.03023087e-02],\n",
            "         [ 2.42676884e-02,  6.85089231e-02, -1.10858582e-01, ...,\n",
            "           1.34609669e-01,  8.94326195e-02, -1.13435751e-02],\n",
            "         [-2.72328649e-02,  5.55700772e-02,  1.29517525e-01, ...,\n",
            "          -1.09261610e-01,  7.70938098e-02,  3.74707840e-02],\n",
            "         ...,\n",
            "         [-5.61484173e-02, -5.34721427e-02, -1.25655502e-01, ...,\n",
            "          -3.98126245e-02,  6.05871491e-02,  6.31657317e-02],\n",
            "         [-1.76663965e-01, -7.99813569e-02, -2.98436563e-02, ...,\n",
            "           2.65537556e-02,  1.08866692e-01,  1.15654200e-01],\n",
            "         [-1.11347817e-01,  9.57486257e-02, -4.70672511e-02, ...,\n",
            "           5.56986369e-02,  1.07329331e-01, -3.17686051e-02]],\n",
            "\n",
            "        [[-5.07460088e-02, -1.72722936e-01, -2.15297472e-02, ...,\n",
            "          -1.03239834e-01, -8.80429149e-03, -7.28413388e-02],\n",
            "         [-4.53381166e-02, -5.72145879e-02, -1.32395133e-01, ...,\n",
            "           3.13988253e-02,  1.28564298e-01,  1.20347766e-02],\n",
            "         [-1.87608778e-01,  1.73194855e-02,  5.22464477e-02, ...,\n",
            "          -1.31231427e-01,  2.46910471e-02, -5.74310198e-02],\n",
            "         ...,\n",
            "         [ 3.90898697e-02, -1.14690699e-02, -1.62004456e-01, ...,\n",
            "          -6.80219904e-02,  3.07185911e-02, -1.80954501e-01],\n",
            "         [-8.64250138e-02, -1.72700211e-01, -2.17237640e-02, ...,\n",
            "           2.94744913e-02,  1.66419566e-01,  1.84605062e-01],\n",
            "         [ 6.61637122e-03,  1.12978024e-02, -1.85498763e-02, ...,\n",
            "           3.44455652e-02,  9.23454240e-02,  2.00633761e-02]]],\n",
            "\n",
            "\n",
            "       [[[-9.62874144e-02, -1.20841026e-01, -1.23552077e-01, ...,\n",
            "          -2.16767918e-02,  8.01691562e-02, -1.68259896e-03],\n",
            "         [-1.01185262e-01,  1.51530011e-02,  5.94753698e-02, ...,\n",
            "           3.60331424e-02,  9.59830210e-02,  1.05058074e-01],\n",
            "         [-1.24590851e-01,  1.63916834e-02,  4.93433438e-02, ...,\n",
            "          -1.46690562e-01, -9.65374261e-02,  1.61707878e-01],\n",
            "         ...,\n",
            "         [ 9.10480469e-02, -3.68207544e-02, -7.95357227e-02, ...,\n",
            "           7.70540163e-02, -6.10602146e-04,  7.08891675e-02],\n",
            "         [-2.24431798e-01, -8.93498212e-02,  2.16930330e-01, ...,\n",
            "          -5.36094494e-02,  1.24587744e-01,  1.75517470e-01],\n",
            "         [-9.41802785e-02,  1.09628201e-01, -1.18484840e-01, ...,\n",
            "           9.98656638e-03,  5.70240244e-02,  3.26362029e-02]],\n",
            "\n",
            "        [[ 4.37180325e-02, -1.36496529e-01, -6.98837414e-02, ...,\n",
            "           1.49135385e-02,  1.30309835e-01, -1.25266556e-02],\n",
            "         [-1.30382493e-01, -5.65586984e-02, -9.40698723e-04, ...,\n",
            "           1.18010521e-01,  1.28922433e-01, -5.19175418e-02],\n",
            "         [ 6.82802647e-02, -5.00323623e-02,  9.85017195e-02, ...,\n",
            "           2.67037563e-02,  1.28514646e-02,  7.73105696e-02],\n",
            "         ...,\n",
            "         [-2.25067157e-02, -7.31948167e-02, -1.09861724e-01, ...,\n",
            "          -4.33141515e-02,  1.99504793e-02,  7.76496250e-03],\n",
            "         [-1.56823441e-01, -1.40766397e-01,  1.96832895e-01, ...,\n",
            "           6.90142140e-02,  1.27311319e-01,  2.23844975e-01],\n",
            "         [-3.53917181e-02,  9.35068503e-02, -1.71207651e-01, ...,\n",
            "          -6.87387735e-02,  1.31876335e-01, -3.92198302e-02]],\n",
            "\n",
            "        [[ 8.56071264e-02, -1.09994560e-01,  7.67658725e-02, ...,\n",
            "           8.41508806e-03,  7.40781724e-02, -1.51983887e-01],\n",
            "         [-1.55232832e-01, -2.23519117e-01, -1.38639197e-01, ...,\n",
            "           5.56674713e-05,  2.74109952e-02, -9.05058831e-02],\n",
            "         [-9.18433666e-02,  5.43854609e-02, -1.17887128e-02, ...,\n",
            "           9.67508033e-02, -5.68989739e-02,  6.63313344e-02],\n",
            "         ...,\n",
            "         [-4.11799550e-02, -1.42969027e-01, -2.40059555e-01, ...,\n",
            "          -1.28767893e-01, -6.13347292e-02, -1.35265023e-01],\n",
            "         [ 2.89545814e-03,  1.82564501e-02,  9.30364951e-02, ...,\n",
            "          -1.96580067e-02,  1.72136113e-01,  8.90038610e-02],\n",
            "         [ 1.93053231e-01,  1.57149017e-01, -7.87426904e-02, ...,\n",
            "          -3.20016481e-02,  1.05209090e-02,  1.31023929e-01]]]],\n",
            "      dtype=float32), array([ 1.34540955e-04,  7.06084189e-04, -1.07323431e-04, -2.30978156e-04,\n",
            "        6.67012704e-04,  2.52927130e-04, -1.30532455e-04,  3.76329001e-04,\n",
            "        3.92537040e-04, -4.74864646e-04,  1.91672982e-04,  3.70919559e-04,\n",
            "        1.35240582e-04, -4.10797511e-05, -2.38029941e-04,  3.50291200e-04,\n",
            "        7.36501068e-04,  4.61845135e-04,  4.71900676e-05, -4.38735733e-04,\n",
            "        1.22263576e-04,  3.38165933e-04, -9.45921754e-04,  1.00103859e-03,\n",
            "       -3.82780017e-05, -9.07581125e-05, -7.75107183e-05, -1.52620359e-03,\n",
            "        9.64455307e-04,  5.84358175e-04,  3.63200030e-04,  8.28862423e-04,\n",
            "        2.32026898e-04,  5.21070790e-04, -5.74590696e-04,  1.38987540e-04,\n",
            "        2.16208591e-05, -3.40440718e-04,  8.56054685e-05,  3.13150871e-04,\n",
            "       -1.00729252e-04,  4.58984490e-04,  6.38282218e-04, -2.05511053e-04,\n",
            "       -6.27840345e-05, -2.20753820e-04, -1.82776697e-04, -1.43012687e-04,\n",
            "        3.87815729e-04, -5.66528412e-04,  1.15809776e-03, -3.71112488e-04,\n",
            "        2.66847230e-04, -6.38042518e-04,  8.75722544e-05, -7.54303590e-04,\n",
            "        3.03317647e-04, -1.37870869e-04, -4.90115082e-04,  1.10101370e-04,\n",
            "        3.71818664e-04, -3.37314996e-04,  1.19990524e-04,  2.74170423e-04,\n",
            "        3.07675335e-04, -8.18672197e-05, -2.92755867e-04,  4.93629137e-04,\n",
            "        7.56125781e-04,  7.61207251e-04, -4.62040072e-04, -8.72712524e-04,\n",
            "        3.94615316e-04,  4.75600071e-04,  1.30538217e-04,  8.95548088e-04,\n",
            "       -3.21195694e-04,  9.53723211e-05,  7.06008461e-04, -4.19661403e-04,\n",
            "       -3.25099303e-04, -5.21229696e-04, -7.62439042e-04, -4.11576621e-05,\n",
            "       -8.64615897e-04,  2.07970108e-04,  6.07803464e-04,  3.98808479e-04,\n",
            "        7.55779503e-04, -1.74290675e-04,  4.63980366e-04,  1.99258153e-04,\n",
            "        7.11473040e-05,  1.08835215e-04,  5.86439681e-04,  1.25014194e-04,\n",
            "       -4.98606649e-04, -2.15062100e-04,  2.43678936e-04,  9.14132761e-05,\n",
            "        1.55235160e-04,  2.87373201e-04, -1.39859039e-04,  2.84848851e-04,\n",
            "        4.08594991e-04, -9.71306436e-05, -2.58647546e-04, -5.56755986e-04,\n",
            "        2.27962955e-04, -6.45182270e-04,  1.54064073e-05, -4.54860710e-04,\n",
            "       -4.48941631e-04, -8.51765362e-05, -8.60635540e-04, -6.30349177e-06,\n",
            "       -9.22928913e-04, -5.28290984e-04, -1.85090947e-04, -7.05994826e-05,\n",
            "       -3.53101677e-06,  8.41943664e-04,  2.58973858e-04, -5.56480489e-04,\n",
            "        1.17131303e-05,  3.07785122e-05, -4.04734426e-04,  1.15017996e-04],\n",
            "      dtype=float32), array([1.1658844 , 0.9637051 , 1.141327  , 0.99467725, 0.81714195,\n",
            "       1.0013033 , 0.96384823, 0.8351997 , 0.9238026 , 0.8433547 ,\n",
            "       0.8951917 , 0.67317796, 0.8492257 , 0.9828586 , 0.80634487,\n",
            "       0.8943727 , 0.85787153, 0.91446084, 0.93355757, 0.9922835 ,\n",
            "       0.7805748 , 1.0143437 , 1.0524606 , 0.82123995, 0.94795465,\n",
            "       0.74828714, 0.8931031 , 1.0577881 , 0.96235114, 0.7848996 ,\n",
            "       0.94688404, 0.77558905, 0.9083723 , 0.97653186, 0.8709265 ,\n",
            "       0.90612787, 0.9982652 , 1.1155269 , 0.8410067 , 0.9753972 ,\n",
            "       1.0427245 , 0.9573899 , 1.0642184 , 0.9363497 , 1.0682528 ,\n",
            "       0.8773027 , 1.0086633 , 0.91803324, 0.8615258 , 0.8286119 ,\n",
            "       0.9378991 , 1.0190774 , 0.945757  , 1.0649176 , 1.0982759 ,\n",
            "       1.0483084 , 0.9690609 , 0.87185925, 1.0881798 , 1.0979116 ,\n",
            "       0.86983   , 1.0060709 , 1.005674  , 0.8598933 , 1.0489814 ,\n",
            "       1.0286095 , 1.0548576 , 0.8639068 , 0.9882513 , 0.8483399 ,\n",
            "       0.95331585, 0.8802111 , 0.85378903, 0.85242486, 0.81102157,\n",
            "       1.0390596 , 0.95138985, 0.9954582 , 0.86393565, 1.0335859 ,\n",
            "       0.8290459 , 0.9126999 , 1.024071  , 0.7629909 , 1.1806375 ,\n",
            "       0.9767958 , 1.1171231 , 0.9818882 , 0.6805101 , 1.0540533 ,\n",
            "       0.95786583, 1.0584731 , 0.77031803, 1.0159184 , 0.850185  ,\n",
            "       0.88397163, 0.95113516, 1.0046574 , 0.89000905, 0.7968733 ,\n",
            "       1.1063449 , 1.0394932 , 0.92982614, 0.8706608 , 0.8398612 ,\n",
            "       0.88753986, 0.9433329 , 0.9237317 , 0.9722374 , 1.1763468 ,\n",
            "       0.9591824 , 0.82480055, 1.0207927 , 1.0776181 , 1.0376965 ,\n",
            "       0.9049959 , 1.0379488 , 1.0209975 , 0.99215126, 1.0397227 ,\n",
            "       0.89345735, 0.9455404 , 0.90633893, 0.8890283 , 0.88607943,\n",
            "       0.65333164, 0.7661068 , 1.0356735 ], dtype=float32), array([-0.36497   , -0.49185127, -0.40924895, -0.41035476, -0.28612712,\n",
            "       -0.18170337, -0.38753855, -0.6098319 , -0.41118142, -0.33294925,\n",
            "       -0.44914642, -0.41724172, -0.5278682 , -0.43557927, -0.37724787,\n",
            "       -0.28852084, -0.310736  , -0.4984109 , -0.4118571 , -0.19625425,\n",
            "       -0.5297563 , -0.29867718, -0.46364507, -0.5071402 , -0.5473117 ,\n",
            "       -0.5055977 , -0.46763322, -0.29126555, -0.39308998, -0.33429357,\n",
            "       -0.54895765, -0.4282193 , -0.57740486, -0.19577195, -0.47358844,\n",
            "       -0.5177559 , -0.44081387, -0.28363544, -0.35067698, -0.4266377 ,\n",
            "       -0.3870557 , -0.4726974 , -0.46619925, -0.42421287, -0.45504093,\n",
            "       -0.44863915, -0.26752615, -0.41206363, -0.29380503, -0.26903397,\n",
            "       -0.42603466, -0.4446482 , -0.38500926, -0.44531015, -0.4383414 ,\n",
            "       -0.44520825, -0.3547153 , -0.33345175, -0.29062632, -0.3911882 ,\n",
            "       -0.5657318 , -0.3732718 , -0.29088256, -0.45978692, -0.32401597,\n",
            "       -0.51528305, -0.38637835, -0.40125287, -0.33990344, -0.51626796,\n",
            "       -0.34286228, -0.36590815, -0.42783856, -0.6458371 , -0.4809523 ,\n",
            "       -0.4374242 , -0.41842413, -0.41190287, -0.4422469 , -0.41512796,\n",
            "       -0.44809818, -0.4184409 , -0.41568968, -0.43577075, -0.43622443,\n",
            "       -0.4360578 , -0.28827158, -0.59145576, -0.45236596, -0.6985181 ,\n",
            "       -0.45089492, -0.57719356, -0.47173747, -0.41705325, -0.44782114,\n",
            "       -0.45216087, -0.36231187, -0.27227566, -0.50772387, -0.43064898,\n",
            "       -0.486583  , -0.5173069 , -0.2782474 , -0.5140885 , -0.5470617 ,\n",
            "       -0.49716762, -0.28150406, -0.48125607, -0.38519478, -0.55510294,\n",
            "       -0.5019025 , -0.35798833, -0.3581201 , -0.27568585, -0.22034307,\n",
            "       -0.30733126, -0.3679154 , -0.43192852, -0.34091902, -0.52831334,\n",
            "       -0.5959986 , -0.6453272 , -0.4572761 , -0.39304614, -0.49941182,\n",
            "       -0.39180714, -0.4580513 , -0.3272325 ], dtype=float32), array([-2.4492397 , -2.9690094 , -5.800163  , -6.9740686 , -3.3136652 ,\n",
            "       -0.78481984, -7.7239013 , -2.8384244 , -7.893434  ,  0.2516907 ,\n",
            "        1.375622  , -6.304168  , -2.2808666 , -7.138759  , -4.892224  ,\n",
            "       -4.7907033 , -3.6417515 ,  1.9608923 , -4.2102075 , -5.1742043 ,\n",
            "       -4.1708636 , -5.0892906 , -2.3266752 , -2.9325848 , -8.681353  ,\n",
            "       -2.6271565 , -4.6601267 , -4.57095   , -3.9796052 ,  3.1163743 ,\n",
            "       -6.34964   , -3.912567  , -2.2087624 , -1.4976721 ,  0.15342306,\n",
            "       -2.3520007 , -4.0299473 , -4.988256  , -4.7146707 , -3.3517692 ,\n",
            "       -2.3441982 , -5.858372  , -6.7579274 ,  1.0648509 , -1.3534416 ,\n",
            "       -3.0298696 ,  1.1630819 , -5.5371823 , -3.8509307 , -4.719015  ,\n",
            "       -6.834799  , -8.187766  , -1.6081035 , -0.71296585, -1.8068562 ,\n",
            "       -3.6290054 , -3.2845647 , -0.5980865 , -4.1798644 , -8.168312  ,\n",
            "       -3.6475506 , -6.0402985 , -0.95717204, -6.109163  , -3.588025  ,\n",
            "       -7.800012  , -5.474657  , -7.3477225 , -1.0273873 , -0.92198396,\n",
            "       -5.1388845 , -2.6824582 , -2.832673  , -4.4805202 , -7.4248576 ,\n",
            "       -2.3282404 , -6.467782  , -2.9627006 , -5.4790435 , -2.9812431 ,\n",
            "       -0.14567983,  0.10362618, -2.276378  , -2.6279247 , -4.4488826 ,\n",
            "        0.86545175, -4.5297036 , -4.821841  , -2.553978  , -1.6342415 ,\n",
            "       -3.8148346 , -6.582309  ,  0.48092222, -8.620942  ,  2.1739678 ,\n",
            "       -5.6608434 , -4.4230895 , -7.916152  , -2.2785354 , -2.3833685 ,\n",
            "       -4.2104177 , -2.862652  , -1.7902975 , -4.65519   , -4.125472  ,\n",
            "       -0.26640487, -3.929158  , -4.066778  , -3.3710225 , -5.4312825 ,\n",
            "       -4.0445375 , -2.7100759 ,  1.084098  , -4.7524014 ,  0.57401896,\n",
            "       -1.0695289 ,  8.312067  , -3.5991437 , -4.1930428 , -5.672048  ,\n",
            "       -7.068022  , -3.9795291 , -3.277792  , -2.687297  , -4.382989  ,\n",
            "       -5.5108237 , -4.708687  , -3.585413  ], dtype=float32), array([13.481776 , 20.344904 , 18.867062 , 13.582252 , 15.145717 ,\n",
            "       17.896635 , 14.036747 ,  9.245777 , 11.035902 , 10.626138 ,\n",
            "       16.082144 , 12.895286 , 12.944125 , 17.917236 , 18.636393 ,\n",
            "       21.077156 , 11.996134 , 13.277442 , 11.229587 , 20.510937 ,\n",
            "       16.66414  , 13.013099 , 16.52841  , 10.633746 , 11.696833 ,\n",
            "       12.991498 , 12.606039 , 19.282051 , 18.667706 , 18.55908  ,\n",
            "       11.168566 , 15.789409 , 13.27663  , 16.276722 , 16.461174 ,\n",
            "       12.79382  , 15.105423 , 14.093413 , 14.492808 , 10.833645 ,\n",
            "       13.8805685, 15.5349455, 11.167776 , 19.443403 ,  9.317831 ,\n",
            "       12.081253 , 16.672514 , 10.59994  , 19.868965 , 11.796727 ,\n",
            "       10.612961 , 15.360578 , 17.508036 , 14.5524025, 11.097164 ,\n",
            "       11.251961 , 12.927911 , 10.550102 , 12.855877 , 17.20053  ,\n",
            "       12.050587 , 12.622258 , 24.66277  , 19.97316  ,  9.173089 ,\n",
            "       10.031548 , 11.065117 , 21.6314   , 13.013525 , 14.677136 ,\n",
            "        9.732494 , 14.935349 , 17.147278 ,  9.115968 , 12.229757 ,\n",
            "       13.216084 , 14.861535 , 11.761838 , 14.3230915, 13.626923 ,\n",
            "       13.641574 , 16.13772  , 13.652628 , 13.745587 , 12.016759 ,\n",
            "       10.777973 , 16.917404 , 13.250614 , 14.690558 , 12.862173 ,\n",
            "       14.600205 , 15.028335 , 11.481774 , 12.395343 , 16.47289  ,\n",
            "       13.44689  , 15.318583 , 11.321515 , 10.761554 , 12.140975 ,\n",
            "        8.087786 , 18.225292 , 13.414257 , 11.557868 ,  9.569445 ,\n",
            "       10.957428 , 17.489958 , 16.734467 , 11.939166 , 12.249669 ,\n",
            "       10.790856 , 15.120006 , 16.363935 , 16.966606 , 13.5877075,\n",
            "       15.1097555, 20.328995 , 10.784059 , 15.253937 , 16.257221 ,\n",
            "       11.082031 , 12.454351 , 13.809326 , 17.782913 , 11.922238 ,\n",
            "       17.687609 , 13.206122 , 12.442815 ], dtype=float32), array([[[[-1.45202532e-01,  1.32732749e-01,  1.63037255e-01, ...,\n",
            "          -1.26032218e-01,  9.46723968e-02, -3.07831392e-02],\n",
            "         [ 2.30179317e-02,  3.26152742e-02,  4.42641638e-02, ...,\n",
            "          -2.54060030e-02,  4.53724414e-02, -1.51302209e-02],\n",
            "         [ 2.13686726e-03, -6.69678524e-02, -8.89999345e-02, ...,\n",
            "           4.76143137e-02, -1.11757725e-01, -3.54146548e-02],\n",
            "         ...,\n",
            "         [-3.18319611e-02,  1.44907301e-02,  8.78667086e-02, ...,\n",
            "          -5.04729711e-02, -1.49647426e-02, -1.15556397e-01],\n",
            "         [-4.88749221e-02, -3.22118402e-02,  9.37531143e-02, ...,\n",
            "          -5.69923734e-03,  1.81884896e-02, -6.37818798e-02],\n",
            "         [ 9.06045139e-02,  1.91807196e-01, -2.33844351e-02, ...,\n",
            "           2.07317378e-02, -1.36516392e-01,  1.73495319e-02]],\n",
            "\n",
            "        [[-5.77647015e-02, -2.73377206e-02,  4.44393568e-02, ...,\n",
            "          -1.26391591e-04,  8.25503841e-03,  1.66033767e-02],\n",
            "         [ 8.51340219e-02, -2.99359094e-02,  1.15889542e-01, ...,\n",
            "           1.85770318e-02,  2.74984706e-02, -1.05216786e-01],\n",
            "         [ 1.49149001e-02, -6.49925694e-02, -3.99739221e-02, ...,\n",
            "           2.73734741e-02, -1.41883297e-02, -3.62358429e-02],\n",
            "         ...,\n",
            "         [-9.58120003e-02, -2.03249473e-02, -1.25669658e-01, ...,\n",
            "           8.91083106e-02, -5.62031120e-02, -1.72744282e-02],\n",
            "         [-5.04080132e-02, -1.23209976e-01, -5.69016188e-02, ...,\n",
            "           1.86653614e-01, -8.66498277e-02, -4.40911837e-02],\n",
            "         [ 3.02205561e-03,  1.23238236e-01, -2.19886631e-01, ...,\n",
            "          -9.86292437e-02, -9.05904621e-02,  3.85946222e-02]],\n",
            "\n",
            "        [[ 4.13116962e-02, -3.90810110e-02, -1.67453825e-01, ...,\n",
            "          -1.61335424e-01, -4.21977490e-02, -4.18146281e-03],\n",
            "         [ 7.49337301e-02,  1.99180499e-01,  1.14859074e-01, ...,\n",
            "           3.84007208e-02, -8.49328861e-02,  4.44169417e-02],\n",
            "         [ 2.74510048e-02, -7.01360703e-02, -6.80142418e-02, ...,\n",
            "           1.02628320e-01,  2.49602702e-02,  1.05559424e-01],\n",
            "         ...,\n",
            "         [ 9.12640095e-02, -2.68483534e-02, -1.17939122e-01, ...,\n",
            "          -3.32204811e-02,  1.23398423e-01,  2.01147273e-02],\n",
            "         [-1.01146422e-01, -1.02639064e-01, -1.58594728e-01, ...,\n",
            "           1.30449340e-01,  5.83335152e-03,  1.29158080e-01],\n",
            "         [-2.90189832e-02,  8.96102861e-02,  2.89007579e-03, ...,\n",
            "          -1.11357249e-01,  7.98872337e-02,  1.18942656e-01]]],\n",
            "\n",
            "\n",
            "       [[[-1.09388024e-01, -5.30632585e-02,  6.10834286e-02, ...,\n",
            "           7.74811581e-02,  6.54052645e-02,  1.22454222e-02],\n",
            "         [-2.68172994e-02, -3.61344926e-02, -4.20387238e-02, ...,\n",
            "          -1.16803184e-01,  1.74344797e-02, -2.16310867e-03],\n",
            "         [ 6.26138449e-02,  1.56098828e-01, -3.47406119e-02, ...,\n",
            "           1.67266816e-01, -1.43690586e-01, -2.54920945e-02],\n",
            "         ...,\n",
            "         [ 3.44814733e-02,  8.32587630e-02,  1.82244003e-01, ...,\n",
            "           8.82934183e-02,  1.86677098e-01,  1.85263176e-02],\n",
            "         [-1.26123494e-02, -8.82782415e-02, -6.44296184e-02, ...,\n",
            "          -8.45710631e-04, -2.32977606e-02, -1.08923316e-01],\n",
            "         [-9.67067927e-02, -3.41832526e-02, -6.20861202e-02, ...,\n",
            "           3.31329480e-02, -1.30300373e-01,  4.98133944e-03]],\n",
            "\n",
            "        [[-4.41919453e-02, -3.03488914e-02,  2.75617838e-02, ...,\n",
            "           4.52207662e-02,  1.62880644e-01, -9.40096155e-02],\n",
            "         [ 1.42955538e-02,  2.06086016e-03, -1.25790555e-02, ...,\n",
            "          -1.29669353e-01, -3.86363491e-02, -1.36797220e-01],\n",
            "         [-1.52975484e-03,  2.26036683e-02, -9.45530385e-02, ...,\n",
            "           1.49436325e-01,  9.53336339e-03, -1.72022097e-02],\n",
            "         ...,\n",
            "         [-4.92488779e-02, -3.01050227e-02,  6.16275482e-02, ...,\n",
            "           1.57735705e-01, -2.66105309e-02,  5.71551062e-02],\n",
            "         [ 1.37656610e-02, -5.93563206e-02, -1.41486347e-01, ...,\n",
            "           6.46847636e-02, -1.25007734e-01,  1.80222038e-02],\n",
            "         [-1.46671146e-01,  1.01723643e-02, -2.69184471e-03, ...,\n",
            "          -1.52049452e-01, -3.80662195e-02,  3.09404712e-02]],\n",
            "\n",
            "        [[-1.55258894e-01,  1.37879059e-01, -2.72759110e-01, ...,\n",
            "          -7.57597983e-02,  1.04329869e-01,  9.21733025e-03],\n",
            "         [-3.31401229e-02,  9.61007401e-02,  3.88429966e-03, ...,\n",
            "          -2.15000622e-02, -1.49531767e-01, -9.20756161e-02],\n",
            "         [-8.80160853e-02, -1.91099439e-02, -7.57389516e-02, ...,\n",
            "           7.06105605e-02,  9.11876187e-02,  1.96482260e-02],\n",
            "         ...,\n",
            "         [-1.25987586e-02, -2.81094741e-02,  1.80309638e-02, ...,\n",
            "           3.66841257e-02,  4.75451946e-02, -2.40681469e-02],\n",
            "         [ 8.46212804e-02, -1.10873044e-01, -4.54388186e-02, ...,\n",
            "           9.64379162e-02, -8.62199888e-02, -2.67550815e-02],\n",
            "         [-2.39422143e-01,  1.01254575e-01, -4.27355990e-02, ...,\n",
            "          -1.12936690e-01,  1.18990295e-01,  8.79918039e-03]]],\n",
            "\n",
            "\n",
            "       [[[-1.11454323e-01,  1.28467992e-01,  3.51432152e-02, ...,\n",
            "           4.50441465e-02, -1.97121799e-02, -5.30287297e-03],\n",
            "         [-1.05694681e-01, -1.53428782e-03, -8.60985462e-03, ...,\n",
            "          -1.61647588e-01,  1.59920584e-02,  1.74694769e-02],\n",
            "         [-6.51583746e-02,  4.36287150e-02, -5.12342528e-02, ...,\n",
            "           4.24791947e-02, -8.13281536e-02, -7.78728575e-02],\n",
            "         ...,\n",
            "         [ 7.63083100e-02, -4.49009053e-03,  1.08195283e-01, ...,\n",
            "           2.42385808e-02,  1.26730770e-01, -6.46340773e-02],\n",
            "         [-1.47605196e-01, -4.67530042e-02, -1.84231997e-02, ...,\n",
            "          -1.73261371e-02,  1.97286103e-02,  2.35567195e-03],\n",
            "         [-3.76411481e-03, -3.43573466e-02, -9.57228094e-02, ...,\n",
            "           5.55083565e-02, -1.34623200e-01, -9.02217776e-02]],\n",
            "\n",
            "        [[-3.12366281e-02,  1.88536197e-01, -1.49815589e-01, ...,\n",
            "           1.65223964e-02, -2.92225089e-03, -1.25874847e-01],\n",
            "         [-1.29813865e-01, -3.82967703e-02,  8.08121078e-03, ...,\n",
            "          -1.60006955e-01, -5.92600144e-02,  5.59247471e-02],\n",
            "         [-4.64931279e-02, -4.13077474e-02,  1.11915588e-01, ...,\n",
            "          -2.12458093e-02,  8.85358527e-02, -9.95842442e-02],\n",
            "         ...,\n",
            "         [ 3.92378271e-02, -4.29051109e-02,  9.45174620e-02, ...,\n",
            "           3.79067808e-02, -7.99603313e-02, -6.87775686e-02],\n",
            "         [ 6.52391836e-02, -1.02587260e-01, -1.32302135e-01, ...,\n",
            "          -7.21688867e-02, -2.39258319e-01,  1.32526234e-01],\n",
            "         [ 4.28419672e-02, -1.10318519e-01, -1.90914065e-01, ...,\n",
            "          -2.18671903e-01,  4.28326875e-02, -2.03354493e-01]],\n",
            "\n",
            "        [[-1.57376975e-01,  1.23450473e-01, -3.60690862e-01, ...,\n",
            "           8.26831162e-02,  7.11060464e-02,  3.80908139e-02],\n",
            "         [-1.55292407e-01,  8.32426399e-02, -1.02091655e-02, ...,\n",
            "          -7.63964280e-02, -2.02350482e-01,  9.36765340e-04],\n",
            "         [-1.15830638e-01, -1.65091544e-01,  2.77061798e-02, ...,\n",
            "          -5.02417190e-03,  1.40006989e-01, -1.16144598e-01],\n",
            "         ...,\n",
            "         [-9.60085988e-02, -3.17728259e-02,  1.48149550e-01, ...,\n",
            "           5.17379753e-02,  3.34861726e-02, -3.03303599e-02],\n",
            "         [-4.36251462e-02, -1.31414399e-01, -1.10187396e-01, ...,\n",
            "          -6.11757897e-02, -2.14082316e-01, -3.17999274e-02],\n",
            "         [ 5.57689322e-03,  1.10915685e-02, -1.47225037e-01, ...,\n",
            "          -1.11429699e-01,  1.91692486e-01, -1.47683904e-01]]]],\n",
            "      dtype=float32), array([ 1.00083795e-04, -6.81626785e-04, -9.92891029e-04,  3.06112604e-04,\n",
            "        1.10654037e-04,  4.91660554e-04, -1.58269642e-04, -2.18070156e-04,\n",
            "       -2.41383561e-04, -2.56812316e-04, -4.49335319e-04, -5.72822930e-04,\n",
            "        7.39763345e-05, -1.93044951e-04, -5.34574618e-04,  7.98901019e-05,\n",
            "       -1.14427786e-03, -4.39287163e-04, -4.06367995e-04, -5.31397876e-04,\n",
            "       -2.14426564e-05,  7.55980320e-04,  2.69234617e-04, -1.06874472e-06,\n",
            "        9.46921995e-04,  6.20839768e-04, -3.35898403e-05,  4.20158991e-04,\n",
            "        9.44659405e-05, -5.02081006e-04, -1.01422716e-03,  6.17309415e-04,\n",
            "        1.47013605e-04, -2.84285634e-04,  1.53022571e-04, -2.24015210e-04,\n",
            "        6.03578053e-04, -2.41484580e-04, -7.41120952e-04,  1.50507642e-03,\n",
            "       -3.15094454e-04,  2.90493423e-04, -5.29427547e-04, -4.35171416e-04,\n",
            "       -8.49898614e-04,  4.49691550e-04, -6.51408278e-04,  2.28974139e-04,\n",
            "       -2.34740844e-04, -5.57992142e-04,  4.52591019e-04,  1.90740029e-04,\n",
            "        1.19058217e-03,  6.86049403e-04, -5.27062162e-04, -4.98537993e-05,\n",
            "       -7.05307684e-05, -3.30142211e-05, -7.71136314e-04, -2.80926361e-05,\n",
            "       -4.06551670e-04, -1.43072844e-04,  1.73683366e-04,  3.49730341e-04],\n",
            "      dtype=float32), array([1.049384  , 0.9743216 , 1.2529345 , 0.9569957 , 0.8897885 ,\n",
            "       1.0625588 , 0.94487774, 1.0321417 , 1.2603464 , 0.8057512 ,\n",
            "       0.9134894 , 0.98774445, 1.1259304 , 1.0811023 , 0.9127938 ,\n",
            "       0.97928166, 0.9846412 , 0.97042865, 0.9426118 , 0.96214294,\n",
            "       0.9532755 , 1.0189427 , 0.95595944, 0.9069798 , 0.96229863,\n",
            "       0.99332696, 0.85466504, 0.93429387, 0.92722505, 0.9179913 ,\n",
            "       0.9197594 , 0.95438296, 1.0572485 , 0.8871214 , 1.0280548 ,\n",
            "       0.96623826, 0.8221014 , 1.0180486 , 0.89980733, 0.9963202 ,\n",
            "       1.0195055 , 0.79421824, 1.0485855 , 0.8619753 , 0.98125356,\n",
            "       0.8512262 , 0.99634933, 0.82937074, 1.0730464 , 1.0576113 ,\n",
            "       0.98730135, 0.98793566, 0.85113347, 1.0751168 , 0.903793  ,\n",
            "       0.96307033, 1.0039061 , 0.89346725, 0.88444966, 0.9827494 ,\n",
            "       0.93267137, 0.9059892 , 1.0229387 , 0.79897296], dtype=float32), array([-0.15144879, -0.2883441 , -0.39344385, -0.13162225, -0.33715257,\n",
            "       -0.427685  , -0.27702773, -0.3308364 , -0.35222146, -0.28617045,\n",
            "       -0.24984956, -0.4276838 , -0.33643815, -0.21276887, -0.31914452,\n",
            "       -0.27591294, -0.19585468, -0.22376962, -0.34516352, -0.25398144,\n",
            "       -0.39748555, -0.34154516, -0.14972134, -0.32838932, -0.46308637,\n",
            "       -0.306976  , -0.24823207, -0.32375625, -0.21873534, -0.262914  ,\n",
            "       -0.51009697, -0.26669163, -0.33534256, -0.3848442 , -0.10518351,\n",
            "       -0.09895355, -0.22827391, -0.28167325, -0.38414055, -0.27385065,\n",
            "       -0.36578664, -0.33909315, -0.23790394, -0.46068737, -0.19558913,\n",
            "       -0.31821817, -0.32114714, -0.11258081, -0.4315282 , -0.44266105,\n",
            "       -0.26115838, -0.3834316 , -0.285495  , -0.25969383, -0.2094598 ,\n",
            "       -0.18878026, -0.1255577 , -0.26083073, -0.19471896, -0.35066217,\n",
            "       -0.32867754, -0.4156733 , -0.46499005, -0.4376777 ], dtype=float32), array([ -7.1922693 ,  -4.9317803 ,  -5.3829904 ,  -4.1245203 ,\n",
            "         2.3557148 ,  -1.6901737 ,  -6.0514293 ,  -2.3904638 ,\n",
            "        -3.3129833 ,   3.5194943 ,  -4.4458575 ,  -0.851123  ,\n",
            "        -8.13683   ,  -2.5708575 ,   0.03574132,   0.2780041 ,\n",
            "        -8.076478  ,  -2.468923  ,  -0.14346632,  -0.3953967 ,\n",
            "        -1.2518466 ,  -4.4813824 ,  -9.884302  ,  -1.1458036 ,\n",
            "         0.47990108,  -1.1183387 ,  -0.14325042,  -3.2891903 ,\n",
            "        -1.8575497 ,  -5.219781  ,  -5.5900016 ,  -3.571787  ,\n",
            "        -3.1442456 ,  -3.8846483 ,   1.1958852 ,  -9.761375  ,\n",
            "        -3.1403346 ,  -8.789539  ,  -0.42497745,  -5.7877374 ,\n",
            "        -6.5302825 ,   1.8572941 ,  -3.8637874 ,  -1.3618795 ,\n",
            "        -3.5645084 ,  -0.83908194,   0.76124424,  -7.734393  ,\n",
            "        -3.9866736 ,  -0.6424861 ,  -3.9435606 ,  -1.6005751 ,\n",
            "        -4.383377  ,  -3.5670004 ,   4.3482428 ,  -8.182703  ,\n",
            "        -9.329407  , -10.108915  ,  -0.47250336,   1.793356  ,\n",
            "        -4.2659926 ,  -1.8581136 ,  -2.3336792 ,  -0.40989208],\n",
            "      dtype=float32), array([25.743769, 21.331219, 28.095043, 23.024698, 16.831438, 22.143433,\n",
            "       25.51797 , 19.821398, 32.282967, 25.540623, 24.490423, 20.451557,\n",
            "       18.75887 , 19.99791 , 17.253544, 20.7294  , 22.062687, 20.260374,\n",
            "       18.013878, 22.83234 , 14.56805 , 18.486479, 26.141356, 15.962482,\n",
            "       21.107964, 22.123585, 19.468386, 23.597292, 24.092278, 19.983814,\n",
            "       19.058477, 24.826136, 18.024128, 18.269924, 18.810617, 31.858204,\n",
            "       22.186619, 22.66772 , 18.179737, 24.059614, 22.659409, 23.441425,\n",
            "       24.528894, 16.215899, 21.714657, 20.709814, 27.994112, 30.835623,\n",
            "       23.832603, 21.411087, 19.308537, 18.785995, 19.405119, 21.539804,\n",
            "       21.646555, 25.445438, 25.941936, 30.15806 , 30.840689, 20.08258 ,\n",
            "       18.109447, 17.746914, 21.287134, 14.567319], dtype=float32), array([[[[-0.20715773,  0.00061342, -0.05735867, ..., -0.26065254,\n",
            "          -0.07146572,  0.02635831],\n",
            "         [-0.1840831 ,  0.2090922 , -0.13875477, ...,  0.22052276,\n",
            "           0.10420772,  0.02126656],\n",
            "         [-0.02111214, -0.0130636 ,  0.12743515, ...,  0.0106866 ,\n",
            "          -0.12471582, -0.0563517 ],\n",
            "         ...,\n",
            "         [-0.00437618, -0.09577876, -0.10240916, ..., -0.21260044,\n",
            "           0.03361955, -0.04995985],\n",
            "         [-0.1325044 ,  0.04557814, -0.10280571, ...,  0.12165432,\n",
            "           0.04190803,  0.23678035],\n",
            "         [-0.0490617 , -0.00124621,  0.03882204, ..., -0.00983245,\n",
            "          -0.19332269,  0.06696191]],\n",
            "\n",
            "        [[ 0.0102693 , -0.00379222, -0.1496692 , ..., -0.14960998,\n",
            "          -0.04424617,  0.10019423],\n",
            "         [ 0.03031574,  0.20196395, -0.0976653 , ...,  0.11391771,\n",
            "           0.07844441, -0.12828511],\n",
            "         [-0.20246747, -0.14200187,  0.0846117 , ...,  0.11704101,\n",
            "          -0.16668929, -0.39021832],\n",
            "         ...,\n",
            "         [ 0.128658  , -0.09141465, -0.08897321, ..., -0.12664661,\n",
            "           0.08832342, -0.00816646],\n",
            "         [ 0.03819739,  0.04951248, -0.21172382, ...,  0.06648247,\n",
            "           0.14545308,  0.0155305 ],\n",
            "         [ 0.02312538, -0.0957807 , -0.10380916, ...,  0.02518904,\n",
            "          -0.035742  ,  0.17248675]],\n",
            "\n",
            "        [[ 0.10214006, -0.00901218, -0.09307729, ...,  0.0235604 ,\n",
            "          -0.13093524,  0.09035169],\n",
            "         [-0.12405948,  0.12779738, -0.04853868, ...,  0.11862779,\n",
            "           0.04867326,  0.00613376],\n",
            "         [ 0.02897728, -0.03893093,  0.04409317, ...,  0.28098112,\n",
            "           0.00601207, -0.28676406],\n",
            "         ...,\n",
            "         [-0.11899292,  0.07856541, -0.07314577, ..., -0.07641288,\n",
            "           0.07271167,  0.01138533],\n",
            "         [ 0.11512556, -0.01772263, -0.12681466, ..., -0.05921325,\n",
            "           0.15958612, -0.0208871 ],\n",
            "         [ 0.08863951, -0.01009749, -0.13109045, ...,  0.0400257 ,\n",
            "          -0.0248452 ,  0.18910514]]],\n",
            "\n",
            "\n",
            "       [[[ 0.00180919,  0.04993383, -0.07586547, ..., -0.06035552,\n",
            "          -0.19981149,  0.05966481],\n",
            "         [-0.1821339 , -0.04573477, -0.15075861, ...,  0.20168038,\n",
            "           0.21823043, -0.07611489],\n",
            "         [-0.04872031,  0.06581313,  0.16214909, ...,  0.03730825,\n",
            "          -0.18244818, -0.00100398],\n",
            "         ...,\n",
            "         [ 0.0016001 , -0.00531348, -0.08144658, ...,  0.07108815,\n",
            "           0.15225953, -0.0630323 ],\n",
            "         [-0.10921064,  0.00625587, -0.13381915, ...,  0.04591463,\n",
            "           0.01569289,  0.10339258],\n",
            "         [-0.02870803,  0.09141201, -0.01080392, ..., -0.08185131,\n",
            "          -0.18988433, -0.04040165]],\n",
            "\n",
            "        [[ 0.05074447, -0.03965452,  0.05099478, ...,  0.06349323,\n",
            "          -0.15626028, -0.01045124],\n",
            "         [-0.00311104,  0.13354689, -0.1901277 , ...,  0.13981445,\n",
            "           0.2681179 , -0.08271116],\n",
            "         [-0.28707388, -0.10626557,  0.16496412, ...,  0.04210376,\n",
            "          -0.2358312 , -0.11933135],\n",
            "         ...,\n",
            "         [ 0.11108204, -0.07278006, -0.09846583, ..., -0.0364372 ,\n",
            "           0.04990356, -0.01489239],\n",
            "         [-0.12001108,  0.11873828, -0.0542823 , ...,  0.10649347,\n",
            "           0.12150338,  0.07108416],\n",
            "         [ 0.02272979, -0.0680128 , -0.03060864, ...,  0.12495395,\n",
            "          -0.04238145,  0.01226709]],\n",
            "\n",
            "        [[ 0.03738062,  0.12767462, -0.1228883 , ..., -0.06187066,\n",
            "          -0.1604552 ,  0.03286973],\n",
            "         [ 0.01591045, -0.05058989, -0.1521715 , ..., -0.0290517 ,\n",
            "           0.18787844,  0.05774385],\n",
            "         [ 0.00811424, -0.05645799,  0.13092002, ...,  0.2892638 ,\n",
            "          -0.14372882, -0.26168478],\n",
            "         ...,\n",
            "         [-0.10603761,  0.10563532, -0.13529457, ..., -0.05771626,\n",
            "           0.04031602, -0.06985005],\n",
            "         [-0.03524131,  0.02584778, -0.08083317, ..., -0.02565889,\n",
            "           0.24394178,  0.0443618 ],\n",
            "         [-0.02569138, -0.08026106, -0.15305944, ...,  0.03440119,\n",
            "          -0.09395094,  0.1378034 ]]],\n",
            "\n",
            "\n",
            "       [[[ 0.04606817, -0.00525135, -0.09627103, ...,  0.06767976,\n",
            "          -0.19277327, -0.00277914],\n",
            "         [-0.12420378, -0.19272718, -0.30693245, ..., -0.0301934 ,\n",
            "           0.08110155,  0.02762437],\n",
            "         [-0.03286752,  0.10414686, -0.13448556, ..., -0.08794052,\n",
            "           0.07776441,  0.17149194],\n",
            "         ...,\n",
            "         [-0.09254432,  0.08775056, -0.09197252, ...,  0.00319971,\n",
            "          -0.04038212, -0.13404268],\n",
            "         [ 0.02336144,  0.03201693,  0.05975767, ...,  0.03519519,\n",
            "           0.14311668, -0.03826944],\n",
            "         [ 0.05782605, -0.00238635,  0.01190855, ...,  0.05328447,\n",
            "          -0.14212042, -0.1024918 ]],\n",
            "\n",
            "        [[-0.04110051,  0.06975155, -0.10425761, ...,  0.0813197 ,\n",
            "          -0.113126  ,  0.10790759],\n",
            "         [-0.07181245, -0.11754951, -0.13324676, ..., -0.19291048,\n",
            "           0.15723832,  0.03083367],\n",
            "         [-0.12530681,  0.01106647, -0.00607578, ...,  0.00848916,\n",
            "          -0.0329653 , -0.04536065],\n",
            "         ...,\n",
            "         [-0.05458924, -0.04924889, -0.05303704, ...,  0.07060933,\n",
            "           0.15375403, -0.1113885 ],\n",
            "         [-0.10395503,  0.06840828,  0.05325645, ...,  0.03942908,\n",
            "           0.26418895, -0.01154781],\n",
            "         [-0.01758675,  0.09365402, -0.06370574, ...,  0.21075246,\n",
            "          -0.08047451,  0.00126081]],\n",
            "\n",
            "        [[ 0.0968466 ,  0.02047138, -0.20068128, ..., -0.10993301,\n",
            "          -0.18048663,  0.00997584],\n",
            "         [ 0.16545568,  0.06297117, -0.2420408 , ..., -0.30217877,\n",
            "           0.26648447, -0.04013171],\n",
            "         [-0.0438153 , -0.02432001, -0.00601779, ...,  0.05750191,\n",
            "           0.09864056,  0.03532144],\n",
            "         ...,\n",
            "         [-0.15657316,  0.03298783, -0.21449584, ..., -0.25307834,\n",
            "           0.03599293, -0.10766436],\n",
            "         [ 0.06961451, -0.03171326, -0.01835562, ...,  0.12811491,\n",
            "           0.02823964,  0.03867656],\n",
            "         [-0.09246841, -0.018536  , -0.21909428, ...,  0.16978715,\n",
            "           0.00524156, -0.01959246]]]], dtype=float32), array([-7.0318597e-04,  1.2198036e-03,  3.7155169e-04, -2.7966234e-03,\n",
            "       -4.0608505e-03, -2.0982414e-03,  2.3169734e-03,  4.3060671e-04,\n",
            "       -1.0470263e-04, -2.4007917e-03, -1.0576594e-03, -2.6328070e-03,\n",
            "       -1.5620784e-03, -1.3729808e-03, -3.1387783e-03, -2.5814466e-04,\n",
            "        3.1753207e-05,  8.6802596e-05,  1.5445321e-05, -4.9714791e-04,\n",
            "       -1.7365025e-03,  3.9457671e-05, -7.1684313e-05, -1.0824184e-03,\n",
            "        1.8151281e-04,  6.8371795e-04,  6.6564901e-04,  8.9148519e-04,\n",
            "        1.2546810e-04, -4.5362292e-04, -1.8366337e-04, -1.3549246e-03,\n",
            "       -2.7708858e-04, -7.2979415e-04, -5.2363635e-04, -1.3191595e-04,\n",
            "        2.4706431e-04, -1.0587815e-03, -1.7902518e-03, -1.9659447e-04,\n",
            "       -1.6518161e-04, -1.4902763e-03, -3.6969202e-05,  5.4585573e-04,\n",
            "       -9.0968481e-04,  2.9732464e-04, -4.6069035e-04, -6.1759131e-04,\n",
            "       -1.7471644e-03, -1.1383529e-03,  5.0064945e-04, -7.3155196e-04,\n",
            "       -1.9325435e-03, -1.4804266e-03, -1.2588026e-03, -1.8986040e-03,\n",
            "       -4.0403602e-04, -1.7121082e-04,  1.9770028e-04,  1.6929399e-03,\n",
            "       -1.2438170e-03, -3.7641704e-04, -1.1223481e-03, -1.0367711e-03],\n",
            "      dtype=float32), array([1.0491796 , 0.8183708 , 1.037162  , 0.96880656, 0.9621072 ,\n",
            "       0.9680516 , 0.9703893 , 0.89871645, 0.95008826, 1.0596589 ,\n",
            "       1.1221794 , 0.90653116, 0.9253522 , 0.91516435, 0.9430231 ,\n",
            "       1.0754397 , 0.9649347 , 0.86570144, 1.0176729 , 0.8882316 ,\n",
            "       1.033024  , 0.8697111 , 1.018214  , 0.8148839 , 0.8827817 ,\n",
            "       0.73657906, 0.8867704 , 0.87210476, 0.87946695, 1.025893  ,\n",
            "       0.9663966 , 0.9442261 , 0.81559694, 1.0231853 , 0.8880482 ,\n",
            "       0.9924834 , 1.0007901 , 0.90667796, 1.0474012 , 0.90256685,\n",
            "       0.91460687, 0.8877048 , 0.80430865, 1.0444623 , 0.8448895 ,\n",
            "       0.83874273, 1.097568  , 1.0379379 , 0.9816539 , 0.9785244 ,\n",
            "       0.9773872 , 0.93389416, 0.9388386 , 0.98567533, 1.033805  ,\n",
            "       1.0661006 , 1.1008296 , 0.8998768 , 1.1185015 , 0.9188387 ,\n",
            "       1.1289897 , 0.87356716, 0.9578928 , 0.8608886 ], dtype=float32), array([-0.343405  , -0.3570059 , -0.38662794, -0.25927716, -0.2966756 ,\n",
            "       -0.50355285, -0.27446863, -0.41140726, -0.50551724, -0.29302853,\n",
            "       -0.3904996 , -0.5617352 , -0.33471388, -0.3813757 , -0.35814846,\n",
            "       -0.43223467, -0.36305946, -0.38550705, -0.30825755, -0.19503282,\n",
            "       -0.24842323, -0.35528967, -0.29755142, -0.38425136, -0.28083372,\n",
            "       -0.40982443, -0.47019562, -0.39558944, -0.33095396, -0.35082892,\n",
            "       -0.35356918, -0.29638118, -0.34766582, -0.6122587 , -0.35787097,\n",
            "       -0.36140683, -0.67536217, -0.4417097 , -0.37541473, -0.29713145,\n",
            "       -0.4204323 , -0.3450154 , -0.4055571 , -0.6231705 , -0.44229716,\n",
            "       -0.55095625, -0.4609979 , -0.5779227 , -0.4457837 , -0.24750735,\n",
            "       -0.34092677, -0.39722946, -0.46937558, -0.3253763 , -0.2603757 ,\n",
            "       -0.5392384 , -0.4928125 , -0.32576323, -0.43221307, -0.30905357,\n",
            "       -0.54464555, -0.16931403, -0.33232749, -0.56336695], dtype=float32), array([-1.697694  ,  0.47700986, -2.1466594 , -0.57948416, -1.6147861 ,\n",
            "        0.12890421, -1.4902371 , -1.376108  , -1.8825985 , -1.6879317 ,\n",
            "       -2.5088613 ,  1.4740056 , -1.6876513 , -1.2930497 , -1.5420969 ,\n",
            "       -2.631726  , -1.0534438 ,  1.5645121 , -1.9286964 ,  0.93981075,\n",
            "       -1.0875347 , -1.9382244 ,  1.0904487 , -1.6695738 ,  0.2689287 ,\n",
            "        1.0781205 , -1.690397  , -0.83099043, -1.3513254 , -3.626856  ,\n",
            "       -0.45772648, -0.4331943 , -0.17877239, -2.3468075 ,  0.19327532,\n",
            "       -1.8172204 , -1.0319548 , -0.89359707, -2.591825  ,  0.71902704,\n",
            "       -2.082468  , -1.4371406 ,  0.5996461 , -1.2034835 , -0.4972826 ,\n",
            "       -1.3065318 , -1.6878426 , -1.2697105 , -1.558163  , -2.7780292 ,\n",
            "       -0.24252293, -0.8633017 , -1.0424694 , -0.85390043, -2.2100658 ,\n",
            "       -0.5345639 , -1.8520551 , -1.2386882 , -1.3699214 ,  2.2824156 ,\n",
            "       -1.3967224 ,  1.3384756 , -0.84995735, -1.7249395 ], dtype=float32), array([3.3264318, 2.8947053, 4.13989  , 3.7669876, 2.8113399, 3.435196 ,\n",
            "       3.6693604, 2.8449328, 4.1958585, 3.6402783, 3.3327224, 4.980507 ,\n",
            "       3.5786436, 3.489088 , 3.7699616, 3.6163886, 3.4595087, 4.0539474,\n",
            "       3.892327 , 3.9772968, 4.121629 , 4.8808026, 5.679677 , 4.9468055,\n",
            "       4.521695 , 3.1990168, 3.9671307, 3.3872716, 4.5925255, 3.7150257,\n",
            "       4.5484324, 3.6669493, 3.349462 , 4.1324363, 4.210452 , 3.43286  ,\n",
            "       3.1582088, 3.959202 , 4.3824215, 4.117958 , 4.3486686, 4.005567 ,\n",
            "       4.398645 , 3.7031198, 3.311847 , 4.4823704, 3.9140997, 3.4386773,\n",
            "       5.1937475, 4.092883 , 4.2213454, 5.3315835, 3.6553316, 3.7828538,\n",
            "       3.8174703, 3.1964984, 4.1683097, 3.8471944, 3.6533608, 3.584277 ,\n",
            "       3.4159644, 3.8237839, 3.703715 , 3.505563 ], dtype=float32), array([[ 0.00735078,  0.14963408,  0.01110534, ...,  0.10851517,\n",
            "        -0.01353395,  0.0339293 ],\n",
            "       [ 0.04586947,  0.02141031,  0.10490807, ..., -0.09990756,\n",
            "        -0.15005527, -0.01019242],\n",
            "       [-0.09338276,  0.01405673,  0.0188883 , ...,  0.06640275,\n",
            "        -0.09493052, -0.04483493],\n",
            "       ...,\n",
            "       [ 0.01864192, -0.04602082,  0.05500209, ...,  0.00776457,\n",
            "        -0.07626381,  0.03444662],\n",
            "       [ 0.15013929,  0.14595519, -0.08122093, ..., -0.00207302,\n",
            "         0.13924815, -0.01686349],\n",
            "       [ 0.10073467,  0.07701489, -0.04589642, ...,  0.14087889,\n",
            "         0.07194287, -0.04542292]], dtype=float32), array([-6.94380878e-06,  1.91495346e-05, -5.74268670e-05,  5.16265682e-05,\n",
            "        2.18207751e-05,  3.40594088e-05,  1.09005305e-04, -7.78881658e-05,\n",
            "        2.05133547e-05,  6.02946457e-05,  1.55950518e-04, -3.16653532e-05,\n",
            "        4.82439209e-05, -5.64918228e-05, -7.17719595e-05, -3.55843586e-05,\n",
            "       -2.10145645e-05, -9.08608126e-05, -2.48505457e-05, -2.41627626e-04,\n",
            "       -1.33539070e-04,  1.61356133e-04, -7.90076137e-06, -7.77921741e-06,\n",
            "       -2.53911257e-05,  7.48079110e-05, -8.49042553e-05, -1.96631863e-05,\n",
            "       -3.53244905e-05, -8.73312965e-05, -7.73234860e-05,  7.30193415e-06,\n",
            "        3.64380230e-06,  6.36277255e-05, -1.43946367e-04,  5.08395315e-05,\n",
            "        1.02914628e-05, -1.86334990e-04,  8.61502776e-05, -6.41486913e-05,\n",
            "       -5.66271847e-05,  3.27538699e-04, -6.58421995e-05, -5.99072118e-05,\n",
            "       -1.29565800e-04, -1.35049675e-04,  3.87169275e-05, -6.92158792e-05,\n",
            "        4.92469226e-05, -9.00300147e-05,  8.61193257e-06, -5.91432217e-05,\n",
            "       -4.20373835e-05, -3.59353326e-05, -5.95588790e-06, -1.45214926e-06,\n",
            "       -2.61627392e-05,  8.22834772e-06, -9.58477631e-06, -4.76872701e-05,\n",
            "        6.27078480e-05,  2.54207716e-05, -6.33373793e-06, -3.97004369e-05,\n",
            "        8.29035798e-06, -2.88372285e-05, -4.75303859e-05,  3.88420995e-06,\n",
            "        4.87406178e-05, -8.01858114e-05, -8.47964984e-05,  1.67128383e-04,\n",
            "        6.66902633e-05,  3.44294240e-05,  5.32008489e-05, -2.08731526e-05,\n",
            "        1.82452277e-05, -1.25565139e-05, -9.28975787e-05,  3.47741770e-05,\n",
            "       -2.15440832e-05,  1.29018721e-04, -3.29105023e-05,  6.01411630e-05,\n",
            "       -8.71131924e-05,  7.88108446e-05,  9.83900463e-05,  7.07721920e-05,\n",
            "        6.92376561e-05,  5.73841571e-05, -1.33122056e-04,  4.05567080e-05,\n",
            "        5.71346573e-06, -1.43968800e-05,  1.07425207e-04, -2.94563179e-05,\n",
            "       -3.76744720e-05,  4.69809347e-05, -6.93289621e-05,  8.13341785e-07,\n",
            "        6.84600018e-05, -1.99884234e-05,  1.02705497e-04, -6.41489969e-05,\n",
            "        3.42249295e-05,  4.20757824e-05, -5.09895181e-05,  3.40971346e-05,\n",
            "        1.46980485e-04, -7.21658289e-05,  4.08715714e-05, -1.46893117e-05,\n",
            "        9.65397994e-05,  2.23798816e-05,  7.21160832e-05, -1.12391259e-04,\n",
            "        1.01750993e-04,  3.14301578e-05,  4.78513721e-05,  3.67630964e-05,\n",
            "        5.68432624e-05,  1.90111696e-05,  4.33883797e-05, -5.82718931e-05,\n",
            "        1.20461053e-04,  1.49428124e-05,  1.26323532e-04, -1.32983463e-04,\n",
            "        6.08661430e-05, -6.70850859e-05, -2.92839741e-05,  3.01181444e-05,\n",
            "       -8.91094023e-05, -3.12025404e-05,  4.50189655e-05,  6.28468479e-05,\n",
            "       -1.32836372e-04,  7.77294554e-05, -2.65731032e-05,  5.28294768e-05,\n",
            "        6.42365194e-05,  1.77391812e-05,  9.55503856e-06,  4.49103318e-05,\n",
            "        1.28897795e-04,  6.99171724e-05,  3.67349603e-05, -6.27760019e-05,\n",
            "       -3.95251845e-05, -1.41651122e-04,  6.55801123e-05, -4.35034272e-05,\n",
            "        4.18694799e-05,  5.77277315e-05,  5.35451582e-05,  1.11792862e-04,\n",
            "       -1.04647901e-04, -1.87790029e-05,  8.23055234e-06, -1.12408663e-04,\n",
            "        6.42603554e-05,  2.40591853e-05,  4.23745696e-05,  1.68683873e-05,\n",
            "        5.07668046e-05, -3.35194964e-05, -9.13653130e-05,  9.81953126e-05,\n",
            "       -1.77950515e-05, -3.75672644e-05, -6.08272148e-06,  1.00492274e-04,\n",
            "        9.02243628e-05,  6.92855829e-05,  6.41471051e-05,  3.28844471e-05,\n",
            "        1.13031085e-04, -4.11405999e-05, -2.08311612e-05, -1.11492962e-04,\n",
            "       -2.33060541e-06,  1.14573158e-04,  7.31562905e-05,  6.96474963e-05,\n",
            "        4.22659687e-05,  1.90400082e-04,  1.06876454e-04, -1.25758888e-04,\n",
            "       -6.85064515e-05,  3.54441836e-05,  6.14028177e-05, -1.95401371e-05,\n",
            "       -2.26820316e-06,  5.64803086e-05, -1.23583464e-04,  7.20203243e-05,\n",
            "       -1.11341824e-05, -2.96273811e-05,  1.71459415e-05,  2.19362373e-05,\n",
            "       -5.23513481e-05,  1.57001523e-05,  1.78898390e-05, -2.46588170e-05,\n",
            "       -5.41818081e-05,  5.03491647e-05,  1.12030675e-05, -4.54856490e-05,\n",
            "       -5.93846053e-05,  7.74725777e-06, -1.06126354e-04,  4.70042978e-05,\n",
            "        1.31637426e-04,  2.99527401e-05, -1.11336289e-04, -4.39228352e-05,\n",
            "       -1.91056955e-04,  5.99406449e-05,  1.03771898e-04, -1.26651148e-05,\n",
            "        2.09518585e-05, -3.85217681e-05, -8.44503738e-05,  5.94192425e-05,\n",
            "       -4.18179707e-06,  5.56582163e-05, -6.80277153e-05,  5.69223303e-05,\n",
            "        4.20221986e-05,  9.71958652e-05, -5.05669668e-05, -7.47221420e-05,\n",
            "        3.28371868e-07, -1.05972817e-04, -4.36922528e-05,  1.29615341e-06,\n",
            "       -6.38319107e-05, -1.26652540e-05,  3.15259640e-05,  1.26485975e-04,\n",
            "        1.03107077e-05,  4.05016581e-05,  8.03813236e-06, -6.24172480e-06,\n",
            "       -6.04699562e-05,  3.61710663e-05,  9.28286136e-06,  1.82594813e-05,\n",
            "       -3.86243228e-05, -9.55474607e-05,  3.00031770e-05, -4.57169917e-05,\n",
            "        3.68824076e-05, -1.63054192e-05, -2.30619753e-05, -2.49597288e-05,\n",
            "        1.12130911e-04,  8.92914395e-05,  3.28007118e-05, -5.24651987e-05,\n",
            "        7.94409934e-05, -3.65464621e-05, -2.88246902e-05, -5.55515253e-05,\n",
            "       -8.39664281e-05, -2.38195171e-05,  1.67910657e-05,  1.31691386e-05,\n",
            "       -9.57345983e-05,  1.86039342e-05, -6.23035085e-05,  4.69690895e-05,\n",
            "       -6.92208923e-05,  3.30106850e-05,  4.26360530e-05,  1.59342508e-05,\n",
            "       -4.84871271e-05,  5.01905124e-05, -9.28904319e-06, -6.99808661e-05,\n",
            "        4.31606459e-05, -7.81594208e-05, -8.58558706e-05,  7.51407206e-05,\n",
            "        2.69646898e-05,  1.19827098e-04, -1.18150092e-04, -1.62343749e-05,\n",
            "        1.15391667e-04,  2.28387562e-05,  1.62470769e-05,  2.31275753e-05,\n",
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            "      dtype=float32), array([0.9316941 , 0.86059433, 0.97130275, 0.7753037 , 0.97660375,\n",
            "       1.027833  , 1.1275315 , 1.0333856 , 1.0502992 , 0.8902131 ,\n",
            "       1.0410169 , 0.85975426, 0.91634434, 0.877447  , 0.98522264,\n",
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            "       1.0164536 , 0.9924906 , 1.0026307 , 1.0881922 , 0.9571282 ,\n",
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            "       0.9394208 , 1.0860828 , 1.1640685 , 1.0043917 , 0.89533794,\n",
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            "       1.0916357 , 0.9469495 , 0.94816434, 0.93097574, 0.948716  ,\n",
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            "       0.90787023, 0.9124177 , 0.82131195, 1.0258471 , 0.989904  ,\n",
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            "       1.0394338 , 1.0655636 , 0.9820711 , 0.88753116, 0.9816405 ,\n",
            "       0.85575384, 1.1458015 , 1.0645059 , 0.9920354 , 0.91717845,\n",
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            "       0.96715575, 0.9368008 , 1.1582658 , 1.0620776 , 0.9529703 ,\n",
            "       0.92686903, 1.0149901 , 1.0217851 , 1.0084422 , 0.99113965,\n",
            "       1.0379343 , 1.0340327 , 0.9485778 , 0.94807714, 1.113566  ,\n",
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            "       1.0392524 , 0.9313505 , 0.9320938 , 0.9993065 , 1.0036639 ,\n",
            "       1.0514295 , 1.1607445 , 0.9448347 , 0.8130268 , 0.964676  ,\n",
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            "       0.96749175, 0.9433355 , 1.0864313 , 0.94562817, 0.79348755,\n",
            "       0.9906104 , 0.95766455, 0.94259447, 0.99572563, 0.9562094 ,\n",
            "       1.1267037 , 0.8858077 , 1.0463358 , 1.0129688 , 1.052655  ,\n",
            "       0.86811495, 0.9177074 , 1.2039654 , 1.004021  , 1.0338323 ,\n",
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            "       0.81133217, 0.8482562 , 1.2558262 , 0.98625565, 0.9879091 ,\n",
            "       0.9968309 , 0.99904454, 0.9321806 , 0.90292335, 1.0240126 ,\n",
            "       1.0708275 , 1.0213826 , 0.9344558 , 0.8039793 , 0.88880706,\n",
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            "       0.9748303 , 0.9614434 , 1.0263083 , 1.1101414 , 0.966682  ,\n",
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            "       1.2214167 , 0.9704842 , 0.847312  , 1.0929499 , 0.98938453,\n",
            "       0.9736303 , 1.0111773 , 1.0511643 , 0.9753292 , 1.1705762 ,\n",
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            "       1.0365994 , 0.9498418 , 1.02303   , 1.116497  , 0.924116  ,\n",
            "       1.0466024 , 0.8860704 , 0.9393053 , 0.9508293 , 0.9462994 ,\n",
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            "       0.9785663 , 0.91671246, 1.0742618 , 0.9893625 , 0.9593675 ,\n",
            "       0.76214945, 1.0314957 , 1.0639772 , 1.0350674 , 1.042088  ,\n",
            "       0.9613314 , 1.0260222 , 0.9140584 , 1.058968  , 1.020086  ,\n",
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            "        4.41171217e+00, -1.73113787e+00, -8.34051907e-01,  5.25648689e+00,\n",
            "        3.34837675e+00, -1.05572309e+01,  4.47031403e+00, -1.59560370e+00,\n",
            "       -3.00400448e+00,  9.31029737e-01, -4.37341213e+00,  1.02551975e+01,\n",
            "       -3.56009698e+00,  7.28561580e-01,  3.88893652e+00, -3.02743387e+00,\n",
            "        5.85196352e+00, -4.79815340e+00,  4.92894173e+00, -5.89101982e+00,\n",
            "       -1.83475649e+00, -5.36416149e+00, -6.87107325e+00, -5.75765252e-01,\n",
            "       -1.14090710e+01, -7.72139835e+00, -1.29794741e+01, -6.72987413e+00,\n",
            "        3.43332982e+00, -1.62752998e+00, -4.30975866e+00, -7.06551492e-01,\n",
            "        4.21494722e+00, -1.03450756e+01,  6.49958551e-01,  3.03493166e+00,\n",
            "       -3.51559496e+00, -6.67383051e+00, -4.22291327e+00,  6.20295620e+00,\n",
            "       -3.78357935e+00, -4.83352423e+00,  6.23902142e-01, -1.48409109e+01,\n",
            "       -8.26351643e+00,  6.69391096e-01, -7.27889419e-01,  8.62102890e+00,\n",
            "        6.61721468e-01, -3.38145947e+00, -4.97113848e+00,  6.48636150e+00,\n",
            "        6.97281837e+00, -3.17489576e+00, -4.43034077e+00, -1.95147455e+00,\n",
            "       -4.38616705e+00, -5.97571358e-02,  4.92338324e+00, -1.16670015e-03,\n",
            "       -1.37981329e+01, -5.88385487e+00, -6.02699804e+00, -2.54541492e+00,\n",
            "        1.30961597e+00,  1.68579140e+01, -2.44427657e+00, -7.90478563e+00,\n",
            "       -1.05849648e+00, -4.37616110e+00,  1.31730585e+01,  1.50006324e-01,\n",
            "       -1.19473038e+01,  1.78292000e+00, -3.07582283e+00, -8.41438293e+00,\n",
            "       -4.77619743e+00, -3.09640408e+00, -9.55694485e+00,  4.56223774e+00,\n",
            "       -3.48627210e+00, -7.92895317e+00, -5.37745142e+00,  2.88260508e+00,\n",
            "       -1.34567184e+01, -1.13845921e+01,  6.07657862e+00, -1.46085179e+00,\n",
            "       -2.35765290e+00,  9.11717987e+00, -1.26214962e+01, -8.98126793e+00],\n",
            "      dtype=float32), array([46.273804, 42.26908 , 26.84378 , 26.796715, 28.711164, 24.695032,\n",
            "       30.884542, 38.587215, 31.709318, 36.6083  , 24.915161, 23.713018,\n",
            "       34.71355 , 33.29488 , 48.45217 , 35.097404, 30.902893, 27.686646,\n",
            "       27.115067, 26.372768, 37.03253 , 31.106071, 31.357475, 28.80351 ,\n",
            "       30.686699, 28.297588, 28.407421, 39.432644, 33.43421 , 34.42224 ,\n",
            "       32.427086, 37.720158, 26.057243, 37.406437, 21.159878, 24.80974 ,\n",
            "       35.715435, 28.747837, 35.797234, 32.682987, 29.7087  , 24.267204,\n",
            "       24.899187, 25.703821, 29.334393, 22.726114, 38.8324  , 27.130333,\n",
            "       32.730793, 22.802984, 22.376955, 30.21229 , 32.69496 , 31.64796 ,\n",
            "       27.899199, 34.966213, 32.91641 , 29.122694, 22.286943, 38.538994,\n",
            "       40.878227, 30.515804, 33.709713, 33.41476 , 28.891928, 27.643396,\n",
            "       28.548864, 27.328384, 38.015873, 41.847527, 24.327372, 26.555532,\n",
            "       24.123432, 29.130297, 27.781858, 31.369404, 58.258236, 46.30083 ,\n",
            "       27.077454, 34.441967, 29.2107  , 25.318768, 34.76818 , 35.715126,\n",
            "       29.969303, 29.69086 , 38.41317 , 43.275757, 30.186615, 31.082687,\n",
            "       26.14032 , 44.08045 , 35.293213, 27.1512  , 54.344963, 33.936394,\n",
            "       24.228212, 34.518898, 48.150814, 27.99733 , 25.301416, 37.750984,\n",
            "       41.766865, 29.898014, 32.213104, 42.319168, 25.75307 , 31.434647,\n",
            "       36.646423, 36.58747 , 34.841812, 32.236023, 37.88151 , 39.55371 ,\n",
            "       36.98964 , 36.927273, 26.50887 , 39.72378 , 38.057526, 36.734035,\n",
            "       29.160542, 46.02833 , 42.833138, 26.000834, 28.418928, 29.928974,\n",
            "       29.903023, 27.952969, 31.56286 , 39.93407 , 21.776957, 21.874565,\n",
            "       27.09099 , 40.12093 , 38.924656, 29.688007, 38.61722 , 33.097004,\n",
            "       29.995588, 37.160942, 25.972672, 42.260906, 33.67451 , 34.92066 ,\n",
            "       32.95052 , 32.21418 , 26.639393, 27.659004, 26.56467 , 24.223373,\n",
            "       29.52711 , 32.800964, 25.995497, 43.81125 , 32.453392, 41.108536,\n",
            "       39.75962 , 28.518568, 30.555721, 31.227514, 30.70212 , 40.74814 ,\n",
            "       23.728302, 44.39042 , 26.149633, 32.597084, 24.38458 , 33.76392 ,\n",
            "       29.73034 , 40.113194, 54.744778, 24.420946, 27.082493, 38.29415 ,\n",
            "       45.88588 , 27.16209 , 35.773243, 30.973902, 30.821152, 36.35449 ,\n",
            "       21.661358, 34.91532 , 26.51806 , 38.746704, 52.47225 , 46.749706,\n",
            "       32.823025, 26.803484, 40.605892, 29.288662, 34.00086 , 31.63325 ,\n",
            "       28.768559, 35.31923 , 26.734108, 37.88742 , 30.790213, 20.827805,\n",
            "       25.110355, 36.830494, 39.4973  , 37.846184, 37.566513, 35.030212,\n",
            "       27.92145 , 48.52817 , 34.411037, 37.089195, 50.069477, 36.357967,\n",
            "       33.329933, 32.616955, 29.585783, 26.208113, 41.12142 , 42.923492,\n",
            "       47.538597, 23.629444, 41.78337 , 25.146091, 25.332712, 33.149345,\n",
            "       30.04274 , 37.23994 , 36.314983, 29.366447, 46.190018, 29.392849,\n",
            "       26.848389, 28.251661, 40.642796, 32.33659 , 29.87569 , 35.490734,\n",
            "       47.62895 , 26.046103, 26.276398, 37.020153, 30.308296, 30.499891,\n",
            "       25.153896, 35.875446, 34.38576 , 32.41821 , 47.14506 , 33.230595,\n",
            "       26.862276, 28.0417  , 43.070152, 24.258577, 29.282679, 37.874756,\n",
            "       51.207676, 28.332075, 25.22131 , 35.857006, 34.95789 , 45.392002,\n",
            "       30.844776, 33.24252 , 40.887577, 31.119429, 34.089798, 53.058853,\n",
            "       28.666636, 37.46214 , 31.802345, 26.544695, 30.04498 , 33.472145,\n",
            "       34.371136, 26.75391 , 41.47438 , 31.329548, 37.6835  , 37.322754,\n",
            "       28.405054, 28.152515, 37.72237 , 44.662804, 20.240911, 28.65091 ,\n",
            "       24.699324, 25.28801 , 24.669676, 33.12189 , 28.700249, 27.680967,\n",
            "       31.31578 , 41.11504 , 23.981848, 31.027016, 27.577158, 31.585941,\n",
            "       42.09153 , 25.805511, 28.342264, 32.98581 , 39.15688 , 31.351742,\n",
            "       41.081158, 29.975573, 32.393543, 23.555605, 36.45549 , 34.275543,\n",
            "       27.847189, 26.887127, 40.656994, 39.081566, 39.386616, 35.55155 ,\n",
            "       37.35617 , 29.120855, 24.639376, 28.412226, 29.634872, 26.724518,\n",
            "       27.347115, 33.991665, 35.474503, 42.88445 , 37.76847 , 36.97188 ,\n",
            "       30.505583, 40.75157 , 31.39854 , 28.26503 , 28.674149, 47.49191 ,\n",
            "       32.419292, 40.040073, 30.146584, 36.769295, 26.687475, 27.494444,\n",
            "       24.877596, 33.383797, 27.935345, 26.93097 , 27.00643 , 40.86812 ,\n",
            "       29.123987, 30.863058, 34.261677, 43.61288 , 33.04979 , 32.3657  ,\n",
            "       28.410757, 34.296986, 24.424139, 28.24632 , 33.479317, 28.099525,\n",
            "       35.311787, 32.85776 , 28.679285, 38.81631 , 30.478601, 31.138178,\n",
            "       40.913605, 24.200697, 30.354315, 24.943394, 33.710136, 28.054325,\n",
            "       42.208588, 26.30218 , 73.02387 , 29.899767, 24.97076 , 24.186224,\n",
            "       37.705456, 30.714682, 31.661594, 29.37151 , 40.340977, 26.269676,\n",
            "       22.906435, 36.80586 , 30.445398, 32.192932, 29.794064, 36.818256,\n",
            "       42.357723, 30.91105 , 41.562126, 34.516914, 28.891497, 27.297323,\n",
            "       39.474865, 27.469633, 26.424831, 28.878048, 33.420105, 60.285244,\n",
            "       28.410477, 25.782707, 32.129627, 30.737844, 25.909916, 25.040213,\n",
            "       28.82809 , 32.492855, 30.219658, 39.461662, 58.321987, 31.725407,\n",
            "       27.205519, 39.229904, 40.932144, 30.1279  , 29.20214 , 38.801476,\n",
            "       32.60256 , 26.809122, 33.987553, 26.10779 , 23.596106, 36.937687,\n",
            "       29.157747, 37.232304, 37.32463 , 29.58566 , 26.379019, 36.06484 ,\n",
            "       31.44396 , 25.019684, 23.380194, 41.072712, 32.33743 , 34.788937,\n",
            "       21.840673, 29.852686, 28.498127, 22.861433, 22.873716, 31.32157 ,\n",
            "       25.043507, 31.092031, 36.17206 , 34.12692 , 26.34961 , 28.683983,\n",
            "       59.18914 , 37.22921 , 39.84897 , 34.383064, 28.738914, 47.157253,\n",
            "       38.038242, 41.439377, 29.784382, 26.566345, 27.019825, 39.92176 ,\n",
            "       43.975395, 25.989386, 23.904541, 28.422695, 28.725075, 24.286526,\n",
            "       35.75001 , 32.754112, 42.186665, 18.105247, 25.0553  , 24.254887,\n",
            "       23.156279, 24.338638, 31.181835, 34.029743, 29.020628, 34.215137,\n",
            "       28.093313, 28.520761, 45.386635, 47.4784  , 36.391735, 22.667852,\n",
            "       31.206211, 47.513332, 31.22273 , 30.220537, 39.02782 , 40.54383 ,\n",
            "       42.65891 , 33.98264 , 24.10423 , 24.727312, 30.401756, 24.388954,\n",
            "       30.077023, 32.572098, 38.156715, 25.17412 , 31.387972, 40.48662 ,\n",
            "       33.582325, 30.44451 , 31.002346, 27.060406, 30.44426 , 34.55223 ,\n",
            "       42.738583, 38.964302, 32.18072 , 29.082935, 39.747166, 20.542244,\n",
            "       53.5536  , 33.115105], dtype=float32), array([[ 0.00151926,  0.04961334, -0.01693337, ..., -0.04778458,\n",
            "         0.02602912, -0.10520969],\n",
            "       [ 0.05157959,  0.11903423, -0.19375464, ..., -0.25996786,\n",
            "         0.04378992, -0.07120539],\n",
            "       [-0.05617515,  0.05785163,  0.04713082, ...,  0.07481939,\n",
            "         0.12359516, -0.1477954 ],\n",
            "       ...,\n",
            "       [ 0.02135688,  0.20075063,  0.03741978, ..., -0.00477684,\n",
            "        -0.16880493, -0.13857044],\n",
            "       [-0.05179828, -0.08787124, -0.07112687, ...,  0.00818385,\n",
            "         0.01184221,  0.11299434],\n",
            "       [-0.00625294, -0.00539652,  0.12771568, ...,  0.06586062,\n",
            "         0.14065017, -0.08758472]], dtype=float32), array([-9.05849738e-05, -4.23224810e-05,  1.52187116e-04, -6.42952000e-05,\n",
            "        7.11103712e-05, -6.90587694e-05, -6.86543062e-05,  5.78979743e-05,\n",
            "        3.51327981e-05, -5.25490723e-05, -3.29062204e-05,  6.53550887e-05,\n",
            "        2.31404789e-04, -2.47730131e-05,  7.53117638e-05, -1.28943575e-04,\n",
            "        3.12791934e-04, -2.65243470e-05, -4.12586203e-04, -2.38129534e-04,\n",
            "       -5.26646108e-05, -1.93385582e-04,  7.14265552e-05,  5.52700840e-05,\n",
            "        5.76592938e-05, -3.07772061e-05, -8.78576320e-05,  1.45231397e-05,\n",
            "        1.56197057e-04, -1.65579564e-04, -2.12575454e-04,  3.01755699e-05,\n",
            "        1.72578223e-06,  1.08576405e-05,  3.48145550e-05,  1.62103679e-04,\n",
            "        2.59563269e-04,  1.62382246e-04,  9.03203545e-06,  1.28782107e-04,\n",
            "        6.55492622e-05, -2.50358600e-04, -1.43034951e-04,  1.07586646e-04,\n",
            "       -2.11034479e-04, -1.29308130e-04, -7.31079563e-05,  7.50635736e-05,\n",
            "        1.30074754e-04,  4.76803893e-04, -2.71901605e-04, -3.78431068e-05,\n",
            "        1.06671454e-04,  1.55543530e-04, -1.13952643e-04,  1.24734259e-04,\n",
            "        4.59682724e-06,  1.15869370e-04, -6.71130547e-05,  2.82423898e-05,\n",
            "       -9.83854479e-05, -1.01908345e-05, -1.49033440e-04,  1.73468827e-04,\n",
            "        1.40029602e-04,  2.06716068e-05, -5.91166136e-05,  2.53630660e-05,\n",
            "       -8.11730570e-05, -6.04570778e-05,  2.41675472e-04, -1.20732166e-05,\n",
            "        1.64367899e-04,  4.68933213e-05, -1.13069880e-04,  2.27616765e-04,\n",
            "        1.14151611e-04,  2.02472555e-04,  4.14637580e-05, -2.15129199e-04,\n",
            "       -1.55175469e-04, -8.56086044e-05,  2.59984401e-04,  2.33307292e-04,\n",
            "        2.82989749e-05, -5.74343449e-06, -4.15245813e-05,  6.10250427e-05,\n",
            "       -1.04319399e-04,  1.19813878e-04,  5.33136335e-05,  1.10815861e-04,\n",
            "        8.37693151e-05,  1.74217384e-05, -5.97792750e-05, -3.60653175e-05,\n",
            "        4.48516539e-06, -1.23726699e-04, -1.70340034e-04,  2.72737583e-04,\n",
            "       -8.98918097e-06,  7.85375869e-06, -4.62271828e-06,  6.86775966e-05,\n",
            "        1.86569043e-04,  8.62523211e-06,  6.89843218e-05,  1.31053836e-04,\n",
            "       -1.23192990e-06, -4.10181892e-05, -1.60021053e-04,  1.59190822e-04,\n",
            "        5.67369061e-05, -4.66503407e-04,  6.81636302e-05, -4.99316302e-05,\n",
            "       -9.77475793e-05,  7.33608395e-05, -5.97369872e-05,  4.49597574e-05,\n",
            "        3.28695969e-05,  4.48811152e-05, -5.59949331e-05,  1.24858998e-04,\n",
            "        1.83525641e-04,  1.76715257e-04,  1.86838151e-04, -1.48865429e-05,\n",
            "        1.19327880e-04, -8.25836541e-05,  3.21321510e-04,  2.14112355e-04,\n",
            "        1.72751636e-04,  1.15222792e-04,  2.58871616e-04, -3.36815021e-04,\n",
            "       -1.18794469e-05,  1.35013688e-05,  7.41840049e-05, -1.69845574e-04,\n",
            "        6.55159020e-05,  1.04878018e-05, -1.73934808e-04,  1.08130989e-05,\n",
            "       -1.59151838e-04, -1.70911117e-05,  1.91713756e-04,  1.73426684e-04,\n",
            "        1.08451364e-04,  3.41104314e-04,  2.27228185e-04, -2.73584810e-05,\n",
            "       -1.80710369e-04, -1.06238353e-04, -3.17038852e-04, -5.75406593e-05,\n",
            "       -3.41084924e-05, -3.88435983e-05, -2.74546292e-05,  1.41639131e-04,\n",
            "        7.87071112e-05, -8.72290766e-05,  8.75096011e-05, -4.11935980e-05,\n",
            "        6.49028152e-05, -7.21201868e-05, -1.74823610e-04,  6.48734567e-05,\n",
            "       -1.07166059e-04, -8.89872317e-05,  1.80611212e-04,  6.90098095e-05,\n",
            "       -4.60165502e-05, -8.04840092e-05,  1.75495981e-04, -1.66769431e-04,\n",
            "       -2.70202727e-04, -6.32655065e-05, -8.83411558e-05, -1.81761221e-04,\n",
            "        1.25840292e-04, -2.05981523e-05, -7.24019337e-05,  1.30253352e-06,\n",
            "       -1.96334458e-05,  1.90806913e-05, -2.25981959e-04, -1.69145700e-04,\n",
            "       -6.38505153e-04, -4.59310140e-05,  2.44942872e-04,  1.95484638e-04,\n",
            "       -7.30336396e-05, -1.30477798e-04, -3.02789966e-04,  3.21859989e-04,\n",
            "       -1.49238054e-04,  8.80920707e-05,  3.79118546e-06, -2.30241021e-05,\n",
            "       -2.94945330e-05, -1.83963348e-04,  1.43810190e-04,  8.06943353e-05,\n",
            "       -2.52003607e-04, -1.60791766e-04, -2.06409430e-04,  2.01986142e-04,\n",
            "       -1.10482470e-04,  1.20636651e-04, -3.91562178e-04,  2.13308987e-04,\n",
            "        2.48814613e-05,  7.15356146e-05,  8.70182557e-05, -3.02645312e-05,\n",
            "        9.40999162e-05, -1.00160723e-05,  3.18106147e-04, -2.69865734e-04,\n",
            "        2.33927174e-04, -2.09233840e-05,  1.36458402e-04,  8.37340758e-06,\n",
            "       -1.58165363e-04, -2.75802537e-04, -1.43150217e-04, -9.30056267e-05,\n",
            "       -1.10542578e-05,  1.34545757e-04,  3.76040625e-05, -9.11012394e-05,\n",
            "       -5.19802961e-05,  1.31418628e-05, -2.27867684e-04,  5.36641674e-05,\n",
            "        7.15617134e-05,  2.73210579e-04, -1.34507311e-04, -1.17434131e-04,\n",
            "        1.64334706e-04,  1.55049755e-04, -2.47183954e-04, -6.31126604e-05,\n",
            "       -1.47679020e-04,  2.63137626e-05, -1.21014134e-04, -2.32975974e-04,\n",
            "        1.08672473e-04, -2.57693668e-04, -1.23321384e-04, -7.63582793e-05,\n",
            "       -8.23262671e-05, -2.61445821e-04,  2.00901777e-04, -1.37200586e-05],\n",
            "      dtype=float32), array([1.0187181 , 0.9248779 , 1.1172193 , 0.8769967 , 0.9103698 ,\n",
            "       1.0521404 , 1.0565575 , 1.0070404 , 1.0298256 , 1.0106537 ,\n",
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            "       1.0200849 , 1.1061605 , 1.0176187 , 0.89434403, 1.0889335 ,\n",
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            "       0.9882565 , 0.95699894, 1.1095182 , 0.8572823 , 0.92288405,\n",
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            "       0.96838826, 0.9966852 , 1.0194815 , 1.1638161 , 0.999331  ,\n",
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            "       0.9275633 , 1.0372453 , 0.89196193, 0.9968723 , 0.93882716,\n",
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            "       0.8707342 , 1.1213565 , 0.90409774, 1.0904912 , 0.9927355 ,\n",
            "       0.9875539 , 1.1082547 , 0.89882773, 1.0878222 , 1.12614   ,\n",
            "       1.0530041 , 0.9122793 , 0.97942066, 1.1501453 , 0.9718065 ,\n",
            "       1.0368713 , 1.0546343 , 1.0603133 , 0.97837543, 1.0959818 ,\n",
            "       0.992351  , 0.92017454, 1.0475686 , 0.9737486 , 1.1379974 ,\n",
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            "       1.1233814 , 1.02061   , 0.9524433 , 1.0593594 , 1.0057658 ,\n",
            "       1.0544196 , 1.0740237 , 1.1357864 , 0.93531024, 1.0497452 ,\n",
            "       1.0606217 , 0.96220064, 0.9732888 , 0.9654794 , 1.1010294 ,\n",
            "       0.9639969 , 0.963991  , 0.9496134 , 1.157566  , 0.9581538 ,\n",
            "       0.9775025 , 1.0701135 , 0.91007257, 0.8891122 , 0.96819025,\n",
            "       0.9717308 , 0.8613232 , 0.9981172 , 1.0919809 , 1.0646664 ,\n",
            "       0.9143567 , 0.9309049 , 0.84684074, 0.8945738 , 0.99616015,\n",
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            "        9.160182 ,  8.317007 ,  7.6345487,  8.673437 ,  5.9953065,\n",
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            "        9.198665 , 10.257914 ,  6.4448395,  8.023572 , 11.659461 ,\n",
            "       12.047303 ,  8.433406 , 11.546045 ,  6.744481 ,  5.884167 ,\n",
            "        6.8484106, 10.585527 ,  7.9590464, 15.249799 ,  5.967177 ,\n",
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            "        9.812402 ,  7.714472 , 12.832988 , 12.7432375,  7.498402 ,\n",
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            "        8.798125 ,  6.5091596,  9.327784 , 12.517641 ,  7.4712744,\n",
            "        6.0520005,  8.985306 , 16.10235  ,  9.853042 ,  8.5455885,\n",
            "        6.0401897,  8.666396 ,  5.7629375,  6.9137187,  9.109782 ,\n",
            "        6.86284  ,  6.114539 ,  6.871719 ,  8.668717 ,  7.7977877,\n",
            "        9.459837 ,  6.3158684, 13.600936 ,  9.057991 ,  7.194213 ,\n",
            "       14.117979 ,  8.026145 ,  6.5544405,  6.6606994,  4.921773 ,\n",
            "        8.517701 ,  8.809662 ,  9.110222 , 11.423268 ,  6.39325  ,\n",
            "        5.9167547,  8.015994 ,  9.926259 , 11.19145  , 11.646926 ,\n",
            "       10.694551 ,  5.6018143,  7.580796 ,  7.3134475, 15.510195 ,\n",
            "        6.9864097,  6.4374413,  8.941001 ,  5.5723705,  6.0401206,\n",
            "        6.698187 ,  9.154844 ,  7.489124 ,  7.6465583,  6.6025515,\n",
            "        7.767695 ,  8.247765 , 11.842688 , 15.28211  ,  7.8662834,\n",
            "        9.563792 ,  8.168791 , 10.09687  , 11.383408 , 10.6560955,\n",
            "        8.020257 ,  8.464086 ,  7.7912717,  7.7021728, 16.317572 ,\n",
            "        7.80023  ,  7.761437 ,  5.8252378, 10.423343 ,  8.383533 ,\n",
            "        6.4074054,  7.5891843,  6.3510056,  4.9623604,  6.172694 ,\n",
            "       10.297559 ,  6.2833385,  9.566082 , 10.447458 ,  8.597738 ,\n",
            "        7.162567 ,  6.569186 ,  6.151167 ,  7.7308445, 11.913587 ,\n",
            "        5.170874 ,  7.8161373,  8.763942 ,  8.804907 ,  5.978045 ,\n",
            "       11.328137 , 14.259013 ,  8.987946 , 10.726827 ,  7.433521 ,\n",
            "        8.128552 ,  7.800084 ,  9.792056 ,  9.414281 ,  5.536321 ,\n",
            "        5.2363186,  7.33749  ,  8.227898 ,  7.9176903,  9.951705 ,\n",
            "        7.035363 ,  9.576215 ,  9.228188 ,  8.613933 ,  5.012733 ,\n",
            "        7.105722 ,  9.777173 , 12.811982 ,  7.1642547,  6.9605284,\n",
            "       10.9438925,  6.884037 ,  8.706965 ,  8.307657 ,  9.614424 ,\n",
            "       16.14439  ,  5.860033 ,  7.2327824, 12.172411 ,  7.654789 ,\n",
            "       12.78035  ,  5.955673 ,  8.127081 ,  8.198255 ,  7.7891665,\n",
            "        7.2729883, 14.689561 ,  5.0327067,  6.6172657, 11.481968 ,\n",
            "       11.803448 ,  6.2271667,  9.321233 , 11.307366 , 10.150744 ,\n",
            "        8.356314 ,  4.791256 ,  8.045267 ,  7.7537446,  6.7659507,\n",
            "       11.350575 , 11.926367 ,  7.205844 ,  7.895195 ,  6.816618 ,\n",
            "        8.096025 ], dtype=float32), array([[ 0.09008468, -0.02670544,  0.0205696 , ..., -0.04044559,\n",
            "        -0.16951144, -0.16238758],\n",
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            "        -0.09024253, -0.11729874],\n",
            "       [-0.00054413, -0.11587201, -0.19056648, ..., -0.12745461,\n",
            "         0.05218813, -0.03070406],\n",
            "       ...,\n",
            "       [-0.1897321 , -0.10291594, -0.13343088, ...,  0.00709665,\n",
            "        -0.04770808, -0.13933584],\n",
            "       [ 0.18441786, -0.16993025, -0.27613732, ..., -0.10545583,\n",
            "        -0.08047757, -0.14537606],\n",
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            "      dtype=float32), array([0.8345628 , 0.9689675 , 0.87643844, 0.91009384, 0.9147686 ,\n",
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            "       0.9067119 , 0.9508494 , 1.0423907 , 1.0085514 , 0.9296985 ,\n",
            "       0.9602146 , 0.9262993 , 0.9104105 , 0.90514624, 0.9050605 ,\n",
            "       0.9295215 , 0.9898471 , 0.97100425, 0.843897  , 0.9390136 ,\n",
            "       0.80439544, 0.9249274 , 0.9410838 , 0.9535995 , 0.94026685,\n",
            "       0.9355452 , 0.9866075 , 1.0381634 , 0.8864884 , 0.95502526,\n",
            "       1.0033578 , 0.94910145, 0.91211754, 0.8832047 , 0.9598638 ,\n",
            "       0.8436642 , 0.94791293, 0.8726165 , 0.898999  , 0.98576695,\n",
            "       0.9766979 , 0.93106246, 0.9744351 , 0.93696207, 0.82170945,\n",
            "       0.8712674 , 0.94115025, 0.9274325 , 0.8562469 , 0.8757817 ,\n",
            "       0.938044  , 0.9353573 , 0.91702545, 0.8721045 , 0.8836772 ,\n",
            "       0.9646802 , 0.89346135, 0.98698515, 0.9050141 , 0.84821916,\n",
            "       0.8983893 , 0.8083374 , 0.931533  , 0.8574374 , 0.9782015 ,\n",
            "       0.82141423, 0.9261978 , 1.0163907 , 0.8296109 , 0.9474196 ,\n",
            "       0.91656715, 0.9572167 , 0.90840036, 1.063462  , 0.7344605 ,\n",
            "       0.93665254, 0.9967194 , 0.8536987 , 0.9079914 , 0.95502377,\n",
            "       0.95572174, 0.8770192 , 0.9457138 , 0.8807579 , 0.9080613 ,\n",
            "       0.98097837, 0.83891064, 0.86898875, 0.896776  , 0.8451631 ,\n",
            "       0.94571716, 0.9857385 , 0.9154249 , 0.96096677, 0.8525424 ,\n",
            "       0.84785163, 0.97158664, 0.9447282 , 1.0869966 , 0.79621595,\n",
            "       0.8820472 , 0.9594774 , 0.95140505, 0.9353279 , 0.93052024,\n",
            "       0.9595724 , 0.90451455, 1.0046617 , 0.9962544 , 0.94074464,\n",
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            "       -0.05378551,  0.08955262, -0.10137036, -0.214688  , -0.03736679,\n",
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            "       -0.13771258,  0.08288504,  0.06352501, -0.09765618, -0.19346349,\n",
            "        0.06052449,  0.00218484,  0.09329209, -0.11953439,  0.00962908,\n",
            "       -0.10319385,  0.03054536, -0.04184542, -0.05664198,  0.00599563,\n",
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            "       -0.02114079, -0.06620103,  0.02183311,  0.02553317, -0.1083378 ,\n",
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            "       -0.07596324,  0.06249033,  0.0528501 ,  0.05850368, -0.02898831,\n",
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            "       -0.02495303, -0.5048309 , -1.332306  , -0.8036232 ,  0.9539782 ,\n",
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            "       -1.3578537 , -2.8640962 , -1.3825227 , -1.0578848 ,  0.83498114,\n",
            "       -2.9906511 , -1.7775486 , -2.270696  , -0.03244473, -1.6020596 ,\n",
            "       -1.8446696 ,  0.5364362 , -0.9995608 ,  0.09343927, -0.23975097,\n",
            "       -0.5372518 , -0.9799507 , -2.0072799 ,  0.30801395,  3.0578322 ,\n",
            "        1.2710829 ,  0.14262806, -0.13104688,  0.7600519 ,  0.74602914,\n",
            "        0.8971434 , -0.21662061, -3.7470381 ,  0.60632896, -1.112733  ,\n",
            "       -0.75742894,  1.520588  , -1.5162803 ,  0.8584793 , -0.41779864,\n",
            "        0.8351351 ,  0.5393651 ,  1.022642  , -1.2083275 ,  0.6212138 ,\n",
            "       -1.1650972 ,  0.28383288,  0.24740788, -0.4642226 ,  0.42752326,\n",
            "       -0.9945659 ,  1.1289937 , -0.23302461, -2.1916637 ,  1.9311426 ,\n",
            "       -1.5547273 , -2.2463527 , -0.23807822,  1.0762053 , -0.51888734,\n",
            "        1.8305571 , -0.9255863 ,  0.65656966, -1.2943662 ,  0.42534336,\n",
            "       -1.4299781 , -1.575184  , -0.59238183, -0.40171084, -1.6381817 ,\n",
            "       -1.0996697 , -1.3962097 , -1.6046739 ,  1.0013614 , -0.8584295 ,\n",
            "       -0.59255797, -3.0771825 ,  0.3826246 ,  0.6411676 , -1.5156963 ,\n",
            "       -1.0856323 ,  0.08336063,  1.7993817 ,  0.0355593 , -0.00779683,\n",
            "       -1.9704599 , -0.5380229 , -1.1557287 , -0.34067693, -1.0695263 ,\n",
            "       -2.2587078 , -0.37515903, -1.2873445 , -1.1415192 , -0.9711679 ,\n",
            "       -2.632069  , -2.4006457 ,  0.62593234, -1.8200253 , -1.5499018 ,\n",
            "       -0.17352079, -2.2191658 , -0.43260053, -0.63060325, -1.3101244 ,\n",
            "       -0.32949555,  0.49913117, -0.57495534,  0.85801804, -0.533726  ,\n",
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            "        5.265616 ,  5.582721 ,  5.773178 ,  7.2979965,  5.0407233,\n",
            "       10.000328 ,  8.466785 ,  5.136147 ,  8.571286 ,  5.1690435,\n",
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            "        4.0325675,  5.664655 ,  7.3867717,  5.957471 ,  6.36868  ,\n",
            "        3.794848 , 11.799652 , 11.399811 , 13.903976 ,  5.172759 ,\n",
            "        5.5895133, 10.884224 ,  4.035005 ,  6.134558 ,  3.7978177,\n",
            "        8.850207 ,  6.619561 ,  8.139414 ,  4.8292627, 12.28462  ,\n",
            "        6.00886  ,  5.961568 ,  4.996122 ,  8.029188 ,  4.700856 ,\n",
            "        7.868971 ,  5.2995305,  5.5439806,  5.0845394,  5.914039 ,\n",
            "        2.9791837,  8.71441  ,  4.1928415,  5.4466147,  3.8669233,\n",
            "        7.346822 ,  4.5984197,  4.830373 ,  5.510487 , 11.295632 ,\n",
            "        9.600964 ,  5.8806744,  5.3136263,  6.273462 ,  5.9394   ,\n",
            "        5.676619 ,  4.2035627,  6.85621  ,  5.9866395,  9.117271 ,\n",
            "        3.6037765,  5.7919006,  8.13129  ,  6.737313 ,  7.995139 ,\n",
            "        5.393244 ,  3.879896 ,  7.558071 ,  6.331797 ,  3.9869742,\n",
            "        9.990186 ,  3.9038494,  5.840458 ,  8.400468 ,  5.871399 ,\n",
            "        6.5950947,  5.2030005,  8.603605 ,  8.725677 ,  5.3645744,\n",
            "        6.2364497,  6.5952735,  5.054843 ,  4.730443 ,  5.7884192,\n",
            "        6.0096397,  6.5662313,  5.6997046,  6.7444935,  4.5339017,\n",
            "        4.479262 ,  9.129222 ,  5.930279 ,  8.656453 ,  7.2225738,\n",
            "        8.876016 ,  8.151584 ,  6.0667486,  4.5867386,  6.327868 ,\n",
            "        5.41338  ,  6.085176 ,  6.898277 ,  5.963791 ,  3.7730544,\n",
            "        6.2208457,  6.405629 ,  5.038629 ,  5.7714367, 11.604695 ,\n",
            "        4.9725566,  6.1310067,  3.7121992], dtype=float32), array([[ 1.97698362e-03, -2.41236001e-01,  4.65277918e-02,\n",
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            "        -3.39426510e-02],\n",
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            "         7.61073679e-02, -3.11909039e-02,  1.19652867e-01,\n",
            "         1.35084435e-01],\n",
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            "        -8.47523287e-02],\n",
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            "         1.11602522e-01],\n",
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            "        -1.39900237e-01],\n",
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            "         8.67628977e-02, -2.62058228e-01,  8.88901949e-03,\n",
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            "        -1.07826188e-01],\n",
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}